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Installation and User Guide for DVT Vision Sensors

1. U Q u 76 DUM NATION ec I UU OO A 36 Industrial Protocols Q J Q J Q Q Q J Q Q Q T 105 TNSPeCtiON MOE E 29 lnspecHon Mode 50 Integration uu uuu OA 101 Intellect SoftWare 48 Intellect User Interface J J U U 48 Mal Men EIU IET 48 Result Tabla ir 51 SAUS EE 51 TN 50 Video Display y uman EM 51 Vision TOO TODO cid A E una 51 Intensity Vision Tool u araara aaraa usus saas asa SaasassssaqusssSussaswasusaassusssussasssisa 59 IP Address u I S UU UU A 17 Line Fit Vision TOOl I UU U UU U U U U T u 66 Machine Vision OOOO O 10 Imaging 4 eso am u E a cut a 10 A O 10 lu iuEe Ui EEE X 74 ludice O 71 Measurement uio us uyu siena ua cacaienccccasusoncnasvassckuseascscvasuacdsvevacentessncacsuectaccuestcensicntvactn 44 70 Measurement in Area e eieieee UU UU u aka Ra R RR RR SERRA RR R SER ARR RR SER ARR 4 Ra kenai animai 70 COGNEX 124 Measurement in Circle u u uuu nua s iia Aaa Aap a Ea aiaa aak aaa 70 Minimum Contrast 44 Modbus Master M
2. 103 Modbus Transfer M 103 Object e Tos P 60 63 Object LOCATING EE UU 67 OCR E TTT 79 e O 42 Outlier DiStanc 72 Partial Image Window Q Q Q J Q Q T 35 Password Protection 29 Pattern COUNTING m 60 64 hcurcriles de 67 PatternCount Q Q Q Q Q J J 59 DAA AAA 83 Pixel Counting Vision Tool U J Q J J T J J 59 loclcro 45 o Eassa 10 Play mode UU T 29 Points and Lines 74 Power On Product 32 dizi a A A E aT ET 69 Product parameters Product Graphs dd week eaa 38 40 Product Parameters c ssceecceeseeeeeneseeeeeenaseeeeeeaaeeeeeaeeeseeaageeseeoaaseeeeneaseeeeenaseeseenageesonsseeeenaaeennnes 34 A GDIoomi g s a u aD NSS T 36 Digitizing TIME ui 35 Exposure Ime yy eee E A er eee ei SEAS Tet 34 llo ida 36 Partial Image WiNGOW i sos aaa aaa A lid 35 PrO UCD ii A A A AA 37 A O 33 Product Selectiohi uuu uu IA TN 37
3. Blue Axis A N i Magenta White Arbitrary Con Pure Green Black Green Axis Pure Red Red Axis Figure 49 Three dimensional color space defined by the basic colors Red Green and Blue This definition of the color space defines a new method for thresholding the images The boundaries of the volume that defines the arbitrary color are the new threshold Colors inside that volume are defined to be above threshold Likewise colors outside that volume are defined to be below threshold As an example if an image contains a number of objects of different colors the user needs to learn the desired color Once that happens the user can use a color filter to extract only the desired colors By doing this the learned color will be the only color let through the filter If the color of the object was learned thoroughly the object will be shown through the filter because it is the specified color Pixel Counting Vision Tool Color Vision Tool The Pixel Counting Vision Tool is the basic Color Vision Tool This Vision Tool was introduced previous in the Counting section However we will explain this Vision Tool in further detail for when used on a color Vision Sensor It is called Pixel Counting to emphasize what it does and to highlight the fact that its use is not limited to color systems This Vision Tool learns a color or many colors and determines the number of pixels of that those color s that are found on
4. Q Rana Q 30 Digitizing TIME u uU Uus TN 35 pi 42 104 DVT Spectral Sensor uuu IIS annu aduana ua kan uuu 44 RR Es ARR RR IRR RR RR RR uA 4 RR Ra au 44 Rn au uu uU 34 DVT ViSION SCNSOF A UU E EA TTE 10 DIMENSIONS 2 orte q ie ie idees reo Get adden sasha al 15 inre rsen 21 Otus s kaptay iin a vo biet cared endi dave A ee anes ove h ee ope ope ean eiTe Tue dete vuv redeo v eade Te ss 21 System Comiponents sists eh neh weed ai ait alta EP RR EP RR ERES OS RRR COR ieee eases 27 DVT Visio n SenSOrS 0 E E 10 Edge Width AAPP O 70 COGNEX 123 EdgeCount EE 57 Emulator a UC OO A 52 Erode POUR TN 42 Ethernet Communications DM o a 104 Ethernet Terminal Controller J Q Q Q 104 Exposure Time 34 FeatureCount Q Q Q Q Q Q Q Q J Q Q Q T RR Raga a 58 Foreground Scripts is sssrinin adonna neeaaea aaan iaa aaaea ana inaua i Aranan aana Eaa 87 FOV Balance E 33 Getting jc EE 9 Hardware Setup P aia 21 Identification Vision Tools
5. 55 Intellect Visi n Tools ii Baa etia n A RAE eS 56 Counting Vision Tools for Presence Absence 57 EdgeCounting Count along a Line Vision Tools esee eene ener nre enne 57 FeatureCounting Count along a Line Vision Tools eee nennen trennen nennen nene 58 PatternCounting Count along a Line Vision Tool 0 ce ceeeessesecssecssesecseeseceseeecsaecaeesecsessecnaseecsaecaeeeeeaecaeeaeenees 59 Pixel Counting Vision Tools Intensity and Color Counting eese rennen 59 Blob Counting Count in Area Vision Tools n eren on cnn non conc nono na trennen enne 60 Object Counting Count in Area Vision Tools n nene etre enne nte on cra non coins 63 Pattern Counting Count in Area Vision Tools eese eene nre nennen trennen enne 64 Positioning Vision TO00lS eese eco et eoe sn rra wa uo re oue eoa ea ie eer reed ones Go nere eR Yo pee eee eain Re ivesi took Cosa ain 64 Position along dlrs enel bip edd eer een e Ho aede eret este teca 65 Rotation with Vision Tools Arc and Line Fit n ener nennen nennen nnne 66 Area Positionmg Vision Tools criba ie dde e ete iet 67 Vision Tools used for Specific Inspections 68 Preprocessing
6. Result Table Product1 Gradient Graph EB Show Graph Show All Tools Q Include Allin Table Name Method Output Result o Inspection Trigger 3 Image Acquisition Q R Width 21 761 pixels Angle 1 08 PASS Pass Result Table lt Guest Figure 25 Screen capture of the user interface highlighting the most important areas The Main Menu contains commands to control most of the parameters discussed so far Here we will discuss the functionality of each submenu 48 The File submenu contains commands to open and save product files system files and graph information The file menu also contains log in as well as manage access control and log events The Edit submenu is used to Copy Cut and Paste Vision Tools and Products In addition the edit menu contains the undo command The View menu contains all the different view windows that can be opened in the user interface This includes the Vision Tool Toolbox window the Properties window the Script Debug window the Result Table as well as others If one of these windows is closed selecting it under the view menu make it appear again o Terminal Window Opens an Ethernet connection to the Vision Sensor s system terminal port 3246 for new systems and 5000 for old systems The DVT Vision Sensor can receive a number of commands in this port that give the user access to it without using Intellect By using this terminal window the us
7. LA AUTOMATION SOLUTION PROVIDER mA EH Ei UR W up up cum System CONSEIL DEPUIS 1985 STRIBUTEUR lb il l DI IDA Installation and User Guide For DVT Vision Sensors intellect scssavexi bs YU T 2 rue Ren Laennec 51500 Taissy France Email hvssystemahvssystem com Fax 03 26 85 19 08 Tel 03 26 82 49 29 Site web www hvssystem com AUTOMATION SOLUTION PROVIDER COGNEX System Ez m wm uy up up pp CONSEIL DEPUIS 1985 2001 2006 by Cognex Corporation 2 d Edition First Printing May 2006 All rights reserved Information in this document is subject to change without notice Companies names and data used in examples herein are fictitious unless otherwise noted No part of this document may be reproduced or transmitted in any form or by any means electronic or mechanical for any purpose without the written permission of Cognex Corporation DVT SmartLink EdgeCount FeatureCount and ObjectLocate are trademarks of Cognex Corporation Microsoft Excel Windows Windows 20009 Windows ME Windows XP and Windows NT are registered trademarks or trademarks of the Microsoft Corporation in the United States and other countries Other product and company names mentioned herein may be the trademarks of their respective owners Part Ordering Number DOC INTL Document Control Number MAN 103 REV D Intellect Release 1 3 Table of Contents TADEO COMET
8. AX55 Figure 9 Sample part to be analyzed in two different inspections This would not only add modularity to the process but also would allow for a more precise inspection because now we can zoom in on the part There is not a need to have the entire part in a single image The inspections are then separated into products A product would inspect the left end of the part and another product would inspect the right end In order to determine if there is a problem with the part those products would use a number of Vision Tools For the first product both Math and Measurement Vision Tools are needed to perform the inspection For the second product Math and Measurement Vision Tools are again needed and a label reader Vision Tool OCR Vision Tool would also be required in this case Finally to send out the data communications a system level parameter needs to be configured Regardless of the inspection taking place a data transfer will occur System Parameters As mentioned before the System level of a Vision Sensor controls the overall functionality of the Vision Sensor The main system parameters are inspection mode password protection I O configuration background scripts power on product trigger source FOV balance and communications setup Inspection Mode A Vision Sensor can be taking images for the purpose of inspecting them or simply for displaying them in a user interface It is important to distinguish between
9. G and B as well as the overall distance shown in the image 86 Figure 52 Illustration of the output color difference as the Euclidian distance in the RGB space The Vision Tool reports the distance to the closest of the three colors that in this case have been learned An important consideration about this Vision Tool is that it does not mark the image When the Vision Tool is drawn all the pixels inside it are taken into account for the computation of the average color The user is supposed to utilize this Vision Tool only over uniform areas of the color For that reason image marking is not used because it would mark every single pixel inside the Vision Tool every time This Vision Tool can be set to pass or fail based on five different criteria Maximum Change in Color Data 1 Depending on the color space used it can be the maximum allowable change in Red reflectance Cyan density or Luminance Maximum Change in Color Data 2 Depending on the color space used it can be the maximum allowable change in Green reflectance Magenta density a or C Maximum Change in Color Data 3 Depending on the color space used it can be the maximum allowable change in Blue reflectance Yellow density b or h Maximum Color Difference Is the maximum allowable distance between the sample color and the ClosestColor The Color Difference is computed depending of the color space as explained above Match Color Name This allows the use
10. Network cable unplugged Intel R PRO 100 VE Network Connection If TCP IP is not on the list click the Install button COGNEX 109 Integrated NIC Properties Zl Client for Microsoft Networks M a File and Printer Sharing for Microsoft Networks M Y Internet Protocol TCP IP Click on Protocol then Add shown below Select Network Component Type Select Internet Protocol TCP I P then click Ok see below Select Network Protocol Internet Protocol TCP IP DLC Protocol NetBELII Protocol Network Monitor Driver NWLink IP amp SPX NetBIOS Compatible Transport Protocol COGNEX 110 Windows will then install the protocol and return you to the Network control panel During this installation process the PC may ask for the Windows 2000 CD ROM and will copy relevant files to the PC s hard drive After this is done restart your PC and continue to the Communicating with the Vision Sensor section COGNEX 111 Appendix C Advanced TCP IP The Vision Sensor runs TCP IP over an Ethernet RJ 45 only connection This Appendix provides some advanced information about this setup that may be useful to Network Administrators TCP IP Installation Tips DVT Vision Sensors are shipped with a random IP address which must be changed according to your network When assigning an IP address to the Vision Sensor you need to make sure that it is one that has not already been assigned to
11. Reflectance Calibration The goal of Reflectance Calibration is to have the measured reflectance of the sensor match an external device Color monitoring and 1 D ANSI barcode grading are the Vision Tools that can benefit from this Note that Reflectance Calibration can be performed for gray scale sensors as well as color There are two reasons why you may need to have Reflectance Calibration for color sensors One reason is to have more accurate relative color measurements with Color Monitoring The absolute color values themselves would not be accurate but the relative ones are closer to reality Another reason why you may need Reflectance Calibration is to match two sensors to each other If they are both calibrated with a single target the color values they measure will match For more information on this procedure refer to the Integration Notes section of the DVTSensors website or the Intellect help file Spectrum Calibration Spectrum Calibration is only available for the DVT Spectral Sensor It is the process through which pixel data is translated into wavelength information When working with the DVT Spectral Sensor sometimes pixel information is not descriptive enough so this calibration option is available The process will involve the use of a part or illumination source with known peak wavelengths After the pixel location and wavelength is entered for each of these peaks the system interpolates them to obtain a transformation mode
12. The user needs to create a reference from the inspection Vision Tools to the positioning Vision Tools so every Vision Tool inspects the correct area of the image every time Figure 58 illustrates how to track the part The positioning Vision Tool locates the part and calculates the shift in position with respect to the original position Positioning Vision Tool Inspection d va Vision Tool a O O Figure 58 position reference mechanism The inspection Vision Tools then reference the positioning Vision Tool to find out where the inspection is to take place If the application allows for the use of the most powerful Area Positioning Vision Tools Blob and ObjectLocate or PatternMatch Vision Tools just one Vision Tool can produce all the necessary position references However some of the fastest positioning Vision Tools can only track one type of movement Unfortunately in most cases a part translates in both horizontal and vertical directions and rotates When that happens and the Vision Tools used do not provide complete position feedback the user needs to create a chain of references Vision Tools may need to find the changes in the location of the part in both X and Y directions and then determine the rotation of it In those cases the chain of references is extended to multiple levels Figure 59 shows consecutive images taken from an actual inspection As the images show the part moved If the Vision Tools are to inspect it positioni
13. Vision To l ait Dee e Eee ead e RR RH etd 69 Measurement Vision Tools ss a dd 70 Math Operations Points and Lines Statistics Vision Tools eese enne 74 Defect Detection Vision Tooluu sn areco e e enne nennen nenne tenete entren reiner innen nett tentent nennen 75 Identification Vision Tools miii eret e eene e Pe dunce kiere ence ede eaae epa eee dens 76 Readers eerta EE REPERIO usa OT BIO RERO nia 76 Intro to Color Vision Tools The RGB Color SpAC8 oooocconcccocnonconcnncononononannnonnonncnnco eene nennen trementem rennen 83 Pixel Counting Vision Tool Color Vision Tool sessi enne nnne 83 Color Mornit rig soe e Roe tbe iid aint heh i Ghia e a bien ate ted 86 Foreground Scripts Script Vision Tools nete ennennen etre E EES Er Ea trennt 87 Spectrograph Vision Dool 2 gita eue ea dte eem eot E a teer p 88 Chapter 4 Inspection Application Guidelines 91 Dealing with Color sssveccvessesnscssscecsvatseseecdaseeccdusssteseshsnacovecsesevesssenccdeaseseneessoadevensesscegsssuncctsndsseessseessuenesse 92 Dealing with Part Movement 93 Presence Absence Inspections 95 Flaw Detection INSPecti nS sssss
14. ai eee ere A E E OD A A Su tr KR e Rea uta 76 Mosi D 59 NADA 66 Math Tools au M 74 Msi 44 70 Patt rnCount 3 e EP e e eee deine ese aS u TEE aka RE RP AEES EAE 59 Pixel Counting icm Pret a er etr n te b eec e eere eg idea rd Det ERA d 83 PrEPFOCESSING EATER OIDTLIDIL LIT LDILILLL UU 69 Readersul su aaa ua usa 76 1D Barcode Reader iss aa a A taa 76 PIATTI LEE 78 OCR UH nana nai odd duis au ua w a au na 79 Scripts Foreground A a aaa 87 Spectrograph P 88 TN 65 Vision Tools Parameters 1 e ee ceeiee eei UU IIIa us RR Rasa NN enn uus Rn maa aus naisiin 41 COGNEX 127 White I mage Normalization J Q annua aus 33 COGNEX 128
15. image For the Emulator it means that the next image in the selected sequence is displayed For the Vision Sensor it will trigger the system to obtain a new image In order to determine the function of the Next Image button that is used users need to select the Static Window for the first function or the Video Display for the second function by clicking once on it before clicking on the button The Product toolbar and the Tool toolbar contain similar functionality for products and Tools For products it offers the extra options of showing the result panel explained below creating a new product and saving a product to flash memory Flash memory is the nonvolatile memory where the product should reside in order to remain in the Vision Sensor after the power is cycled Both sections of the toolbar contain a pull down menu with the existing products in the system and the Vision Tools that the selected product contains The remaining toolbar buttons are to duplicate edit parameters delete or access the graphs associated with the product Vision Tool selected from the pull down menu The Video Display is where the images obtained from the Vision Sensor are displayed Not every image from the Vision Sensor is transferred to the user interface For the Vision Sensor the number one priority is to run inspections After that and depending on processor usage it sends images via Ethernet to the user interface In cases where the Vision Sensor is being
16. purpose For more information about SmartLink please refer to the SmartLink User Manual VDX Driver The VDX Vision Data Exchange driver is used as an alternative to Modbus to communicate between Vision Sensors and PROFIBUS or DeviceNet enabled SmartLink devices The SmartLink device as an intermediary will exchange information with a PROFIBUS or DeviceNet master through these networks and will use the VDX driver to relay the information to the Vision Sensor The VDX driver is enabled disabled through the respective options under the I O menu in Intellect For more information about the protocol consult the SmartLink User Manual the Intellect Help Files and the Script Reference Guide 105 Appendix A Emulator tutorial Chapter 2 A Closer Look at the System explains the basics about the use of the Emulator This appendix walks the user through a full example on how to work with it Every step is explained and the Intellect dialog boxes are included for reference If the user already has a set of prerecorded images and a product or system file the first 2 steps can be skipped Step 1 Connect Intellect to the Vision Sensor and create a backup copy of the System or Product files In order to do this the user must select the desired option Save Product As or Save System As from the File menu This will prompt the user for a file name just like in any Windows application A file will be saved to the compu
17. 502 Modbus standard The Modbus Master initiates the connection and decides the type of operation to perform write data to the slave or read data from it Figure 64 shows two possible configurations for sharing data using Modbus transfers The first configuration uses Modbus transfers to exchange data between Vision Sensors There are four Vision Sensors in the DVT network three of them are being used as Modbus slaves and the fourth one acts as the master This Vision Sensor queries the slave Vision Sensors for data and based on the data from all three slaves and its own data draws a conclusion The final output of the inspection is made available to an external device using either Modbus or some other type of communication It could even be a single T O line indicating a PASS or FAIL result The second configuration shows a slightly different setup In this case an external device is acting as a master and the Vision Sensors performing inspections are acting as slaves The external device has direct access to the internal memory of the Vision Sensors so it can easily query the individual inspection results from each Figure 64 Two different configurations to share data among multiple devices In order to make a Vision Sensor behave as a master a Modbus master transfer must be created from Intellect This transfer will indicate the slave IP Address the operation to be performed read write the block of registers to use and the pollin
18. 542c 10 22 50 84 255 255 0 0 00 90 68 01 04 542310681 Vision Se Intellect Version 1 2 2 Build 01 B Ron s 542c 10 22 50 17 255 255 0 0 00 90 68 00 98 542410289 Vision Se Intellect Version 1 2 2 Build 01 ALEX_S45TEST 10 22 50 228 255 255 0 0 00 90 68 01 29 545100004 Vision Se Intellect Version 1 3 0 DEBUG DWT vision Sensor Unknown 10 22 80 224 255 255 0 0 00 90 68 00 7c 545100010 Vision Se Intellect Version 1 3 0 DEBUG Phil was here Up 10 22 50 9 255 255 0 0 00 90 68 00 d2 550220012 Vision Se Intellect Version 1 2 2 Build 01 daves 550 Up 10 22 50 83 255 255 0 0 00 90 68 00 d2 550220034 Vision Se Intellect Version 1 2 2 Build 01 DVT Smart Camera Up 10 22 50 225 255 255 0 0 02 90 68 00 00 552420010 Vision Se Intellect Version 1 3 0 Beta 5 Ens Unknown 10 22 50 66 255 255 0 0 00 90 68 00 f3 9c 558910092 LineScan Intellect Version 1 3 0 Beta 5 D DVT Smart Camera Unkno 192 168 0 255 255 0 0 00 90 68 00 f 5589101 LineScan Intellect Version 1 2 2 Buil kz d IL ALAARA M A A AA AA A A M Figure 6 Network Neighborhood 18 e Highlight the DVT Vision Sensor with the appropriate serial number In the properties window on the right side of the screen is where you can edit the Name IP Address and IP Mask Set the IP address to be same as your comput
19. A B AC X i AB c i i Angle arc length AB Angle Offset ele g aB i D arc length AC line fit red Figure 34 Output calculation for Arc left and Parallelogram right Rotation Vision Tools As the figure indicates besides the angle of rotation the parallelogram outputs a distance That distance illustrated as X in the figure is obtained from the origin line of the Vision Tool That is the first line that the user draws for this Vision Tool acts as a Translation Vision Tool Furthermore the direction in which that line is drawn indicates the direction of the scanning lines This Vision Tool consists of a number of parallel scanning lines Those lines look for edges or features according to user specifications and each one determines a point where they intersect the selected edge feature The Vision Tool then fits a line along those points and tracks its rotation The intersection of that line with the original Vision Tool line is used for translation output Figure 35 shows a sample image where the parallelogram tool is used The square in the upper left corner of the tool indicates where the user started drawing the Vision Tool The arrows indicate the direction of scanning so this tool was drawn starting on the upper left corner going down then it was expanded to the left to indicate the width Fixe Inbarty Posten Aang Graph Pala Figure 35 Use of the Parallelogram tool of the Rotation V
20. Intellect Version 1 2 2 Build 01 DVT 510 DvT vision Sensor 10 22 50 67 255 255 0 0 00 90 68 01 0a 510221708 Vision Se Intellect Version 1 3 0 Beta 5 DVT 510 a Vision Sensor 10 22 50 239 255 255 0 0 00 90 68 01 29 515100001 Vision Se Intellect Version 1 3 0 ALPHA Unknown 0 ion Sensor Unknown 10 22 85 125 255 255 0 0 515100010 sion Se Intellect Version 1 3 0 DEBUG sps535 Up 10 22 50 197 255 255 0 0 00 90 68 01 29 535100001 Vision Se Intellect Version 1 3 0 ALPHA 8 ALEX_S35TEST Unknown 10 22 50 119 255 255 0 0 00 90 68 01 29 535100004 Vision Se Intellect Version 1 3 0 ALPHA piacnostics Unknown 10 22 50 105 255 255 0 0 00 90 68 01 5d 540113356 Vision Se Legend 540 Diagnostics 1 4 0 I DIAGNOSTICS Unknown 10 22 50 105 255 255 0 0 00 90 68 01 5e 540113356 Vision Se Legend 540 Diagnostics 1 4 0 DVT Smart Camera 10 22 50 105 255 255 0 0 00 90 68 01 22 540113356 Vision Se Intellect Version 1 2 2 Build 01 Bed s 540 10 22 50 41 255 255 0 0 00 90 68 00 98 540310667 Vision Se Intellect Version 1 2 2 Build 01 DVT vision Sensor 10 22 50 245 255 255 0 0 00 90 68 00 a5 540311069 Vision Se Intellect Version 1 3 0 ALPHA DIAGNOSTICS M 169 254 1 255 255 0 0 00 90 68 00 c 5403111 Vision S Legend 540 Diagnostics O I color Camera 10 22 50 52 255 255 0 0 00 90 68 00 9f 542310205 Vision Se Intellect Version 1 2 2 Build 01 daves
21. T O 3 MODULE T 8 O Jg O CONNECTORS E m n E 5 z O F gt O u gl O 2 s gt 122 1D Barcode Reader J Q aa annua Q Q Q RR Q J Q Q nna su Ran 76 pi 78 Access Control Password Protection i 22 nette a Dp EO nate ioi het foa bg Deseo gx need 29 Anti blOOMING mee 36 Background SCript 32 49 onec Tus u IU aaa sassa aaan aa aiaia Ea ahaaa ananta anina ianiai anasa niaan ie 60 Blob LOCAatiNG 2 cccceseeeeeeeeeeeeeaeeeeennaeeeeeenaeeeeenaaseeeeeseeseooaeuseaoasseeeenaaseeeeoaaseeseagsesenoagseeeeoesanaaees 67 jrE 42 i 83 Color Monitoring 86 Communications DATO u reer rr terres rice SSS A A S AE SSES a a ree 102 Ethernet Terminal Controller 2 ir aaa 104 Industrial Protocols tirer a i akawa aaa aida 105 Modbu s Master anu sen casey caer da Aa ai 103 Modbus Transfers vicario Lye po ied Pc Pere ria LER PLE Ea Pu de Dag Eee ORAT TE RR ie 103 Dark I mage Subtraction Q J Q J Q Q Q 33 Datalink qUUE 102 Datalink WincdowW ONU TN 49 Digital O Configuration
22. TCP IP communications along with the IP address Without a subnet mask communication will not be able to take place between two network devices The Subnet Mask also helps you to identify what is the Network ID and what is the Host ID in an IP address COGNEX 116 Appendix D Upgrading or Reinstalling DVT Vision Sensor Firmware Before installing Intellect on your PC and upgrading the firmware file in the DVT Vision Sensor take the time to backup the existing system to the PC To back up a DVT Vision Sensor system to a PC e Run the older version of Intellect and connect to the DVT Vision Sensor e Click on the File menu e Choose Save System As in the File menu e When prompted provide a filename e Exit Intellect Now that the old system has been fully backed up Intellect may be installed on the PC To install I ntellect on a PC e Insert the Intellect CD The installation should automatically start e If the CD does not automatically start do the following o From the Start menu choose Run o Type D Setup exe substitute the appropriate drive letter of your CD ROM drive for D and press Enter OR e Run the installation file downloaded from the DVT website e Follow the installation instructions on screen e After Intellect has been installed on the PC the firmware file on the DVT Vision Sensor must be upgraded Upgrading I ntellect firmware on a DVT Vision Sensor Note The DVT Vision Sensor is a stand al
23. These workshops offer an introductory view of both the Camera hardware platform and the Intellect software The ASP Seminar Workshop is a perfect way to get your feet wet on DVT s inspection systems e Intellect Training Courses Comprehensive four day training courses are taught at Cognex s Atlanta and Detroit training facilities as well as other Cognex locations worldwide These courses are a great way to get a quick start on learning Intellect They are free of charge with users responsible only for their transportation dinners and lodging To learn more and to sign up for a class please contact your local Automation Solution Provider ASP or go to http www dvtsensors com training and click on Classroom training for the schedule e CD Rom Self Paced Training DVTTraining com is a website which deliveries training through self paced online training videos and emulator examples This training is available at www dvttraining com and is available for free from Cognex 24 Online Training Weekly 45 minute courses using the latest technology of online conferencing These courses are free of charge as well please contact your distributor for more information Subscribe to the SmartList Join the long list of Camera users who regularly discuss topics via DVT s SmartList server Discussion topics include but are not limited to o Application questions What light source should I use o Intellect software questions Which Vision Tool
24. This ensures the receiving system that new data is transferred as soon as it becomes available The methods of communication that support synchronous transfers are the digital I O discussed under system parameters and DataLink Asynchronous transfers of data happen at a certain rate In most cases the user selects the rate and blocks of data are continuously transferred whether they contain new data or the same data that was already transferred An example of this method of data transfer is the Modbus master transfer available from Intellect It should be mentioned that because of their flexibility scripts allow for both types of data transfers but in this case the user needs to implement the transfers For more information about scripts see the script documentation and help files DataLink DataLink is a built in tool used to send data out of the system and even receive any terminal commands from another device This tool is Product specific that is every product has its own DataLink that can be configured depending on the inspection and the Vision Tools being used DataLink consists of a number of ASCII strings that are created based on information from the Vision Tools By default the datalink string is sent out after each inspection however the user can define a set of rules under which those strings are to be sent out Those rules are created using logical operators and or acting on Vision Tool results and associating them with a
25. Vision Tool can be used to grade the quality of the barcode being printed The method follows ANSI ISO standards and produces a full report for every barcode analyzed For more information on this procedure refer to the Integration Notes section of the DVT website or the Intellect help files This procedure is very sensitive to illumination Before using the Vision Tool for barcode grading system reflectance calibration must be performed see the Intellect help files for more information and review the section on Reflectance Calibration in this manual Two Dimensional Code Reader In Intellect there is one Vision Tool for all 2 D codes This is a rectangular shaped Vision Tool and the user will specify under the Options tab the type of code that will be presented DataMatrix SnowFlake or Vericode for Vericode a license is needed The DataMatrix reader has the following features e Support for all ECC format DataMatrix codes including ECC200 ECC 200 codes can be identified by the even number of rows and columns result is a white pixel in the corner opposite to the intersection of the solid dark edges or vice versa e Automatic detection of symbol size starting at 10x10 including rectangular code densities LEE Figure 45 Different examples of DataMatrix applications labels left printed circuit boards center and other metal parts right The Vision Tool searches for a DataMatrix code inside
26. a particular image For example if the inspection mode was tied to the user interface play mode the Vision Sensor would stop inspecting images every time the user needs to analyze an image in details for which it would be necessary to stop the real time feedback This 50 would cause a problem when other devices depend on the result from the Vision Sensor to accept or reject a part It should be mentioned that Table 6 summarizes what happens upon triggering the system That is when the trigger mode is set to internal with a period the updating of images outputs as set by the aforementioned parameters will occur periodically However if the trigger mode is set to external the updating of those parameters will only occur when the Vision Sensor receives an external trigger In addition to these controls the Image Toolbar contains a Previous Image and a Next Image button The Previous Image button works with the Static Image Window and the Sample Image Display It changes the current image shown to the previous image in the sequence being used The Next Image button acts as an external trigger button When working with an Internal Trigger the next image button changes the current image shown to the next image according to the image sequence when the Play button is not pressed If the system is on external trigger this button is enabled and its functionality affects the Video Display thus the Emulator or Vision Sensor by causing it to go to the next
27. another device on the network Vision Sensors do not require a Default Gateway to be set For more information on what a Default Gateway is please refer to the respective section later in this appendix Typically when connecting your PC to the Vision Sensor the network masks must match The IP address can be changed from Intellect software System menu Network Explorer selection or from the Network Neighborhood Browse see below Network Explorer DER ETA 2 actions T El mo l Network Name Status Group IP Address IP Mask Network Neighborhood rd Wd SmartImage Sensor Up 10 22 50 27 255 255 0 0 E pIaGNosTIcs Unknown 169 254 124 126 255 255 0 0 2 DYT Smart Ca Unknown 169 254 0 1 255 255 0 0 IF Gregs 550 Up 10 22 50 49 255 255 0 0 B Ed_Test530 Up 10 22 173 224 255 255 0 0 B DVT Smart Camera Up 10 22 50 25 255 255 0 0 2 phirs 510 Up 10 22 50 65 255 255 0 0 Cam2 Connected 10 22 50 89 255 255 0 0 2 DIAGNOSTICS Unknown 169 254 41 107 255 255 0 0 Beds 540 Up 10 22 50 41 255 255 0 0 DYT Vision Sensor Unknown 10 22 50 245 255 255 0 0 2 nick s 540 Up 10 22 50 38 255 255 0 0 I daves 542c Up 10 22 50 84 255 255 0 0 nick s 542c Up 10 22 50 37 255 255 0 0 I Ron s 542C Up 10 22 50 17 255 255 0 0 2 DvT vision Sensor Up 10 22 50 242 255 255 0 0 2 Phil was here Up 10 22 50 9 255 255 0 0 E daves_550 Up 10 22 50 83 255 255 0 0 I eLo Demo 10 22 50 34 255 255 0 0 E sandip Emulators E Favorit
28. by the number of defects of a certain size It should be noted that the resulting error image of this Vision Tool can be used as an image reference by other Vision Tools like blob counting so that the flaws can be further processed But user needs to make sure there is no fail condition set for the defect detection tool or image referencing would fail Identification Vision Tools The Identification Vision Tools are used to recognize or identify a particular part or feature from a set of learned parts or features There are two types of Identification Vision Tools Identification and Color Identification The Identification Vision Tool uses blob based properties associated with an object to identify it from other learned objects The Vision Tool finds the object that most closely matches the learned object based on different identification criteria like area eccentricity compactness perimeter intensity radius and color The Color Identification Vision Tool is used to identify an object based on the color content under the Vision Tool The colors found by the Vision Tool are compared against the colors contained in the trained color models Readers Intellect contains a number of Vision Tools dedicated to reading codes labels etc These are the Reader Vision Tools These Vision Tools consist of the 1D Barcode Reader 2D Reader DataMatrix SnowFlake and Vericode and OCR Vision Tool used for Optical Character Recognition and Optica
29. can be used to actually determine the final result They can be set to pass or fail based on how much the part has moved in the image 65 Rotation with Vision Tools Arc and Line Fit When the Position along Line Vision Tool is drawn as an arc the Vision Tool computes the angle of rotation of objects in the image Like line Vision Tools arc Vision Tools allow different positions of an object without failing the part for being in an unexpected position or location In other words other Vision Tools can reference the output of Rotational Vision Tools in the same manner as with line Vision Tools There are two types of Rotation Vision Tools arc based and parallelogram based Arc Based Vision Tools are often applied when the position of an object is known to have fixed radius and center of rotation For example the ball bearings in a race can be moved around a circle but are restricted from moving up and down independently A Circular Arc can be drawn to locate one bearing and other Vision Tools can reference the position output of the Circular Arc Basically the arcs used to track rotations work like translation lines do They search along the arc for a specific edge or a specific feature Then they report the percent offset from the origin of the Vision Tool The difference with translation lines is that besides that percent offset there is a center of rotation associated with the angle being reported That center coincides with the center of
30. eee eee ee etes testen sten tosta stato seta sees sons tn seta sesso seta sesta Essos 121 Reference Materials for DVT Products The Installation and User Guide for DVT Vision Sensors is your basic resource for both our hardware and software platforms This document is designed to provide the users with basic ideas about the functionality of the software Several other reference materials available are the m DVT Vision Sensor Script Reference Guide a manual for the programming language used in all scripts in Intellect m Intellect HTML Help These HTML based help files which will be installed on your PC s hard disk as you install Intellect and are also available from the Help menu m The best source for Intellect training is the DVTTraining com DVTTraining com is a training website that can be used for self paced learning It is a free tool that users can use 24 hours a day 7 days a week at no charge NOTE This guide assumes users are familiar with Microsoft Windows Chapter 1 Getting Started This chapter contains important information for both new and experienced users New users will benefit from general ideas about machine vision as well as from pointers to other sources of information and training This chapter starts with an introduction to the DVT Vision Sensor product family including technical specifications and a brief description of every Vision Sensor in that family including the DVT 5X5 Vision Sensors Line Scan Sens
31. eit 33 POW Balance eonim RO ERE Pr ORE EE E E deo Sere rn 33 Sensor Gan dst ee de v e ee ame dde mt edet 33 Reflectance Calibration bla 34 Spectrum Calibrations nn E 34 Product Parameters ratita Ra O caido Recs 34 Exposure mie x rait teo toe gh tie 34 Digitizing Time tenore Sp ARI Sep I bei RU Rte Sasu 35 Partial Image Wandow y A poet 35 Antiblooimmeg n upas bog ata rain cot ted abeo atit bo BU oi S p eiiis 36 o NON 36 Product Identification 4 ne e tr p eet a RT EA ys Ae 37 Product S lection a ts nete A epar ebat A A tec eti 37 NN A ioo no ee REGES p bg e eee E Ger ie EHE Sereni 38 Product Graphis rias wed emt f i entes 40 Vision Tool PAPAMNClON rondan rias 41 Vision Tool Shape saus usa a u aah at been e ia 41 PreProcessiligOperations tt eh n ide Qu iba e u e m di RC EE rue o vin AER de aypa 42 PES TON esis a us 43 Vision Tool Res lt eene eaece deni cde re eee Ern edi Tenet RI ere ee ede e Tea 44 Visi n Tool Graphs u n eiue doe oti i edet ie e datei dde e P dee 45 Dueirtal Rele rn ee ehe e ee tee ti ec e e vec ente dete decr Goud ede e et e y ed d d t tn 47 aa Pl 48 Intellect User Interf ce a a pr eee ame FORO eeu me tee tite tO 48 DVT Vision Sensor Hardware Emulator esses nennen nennen 52 Chapter 3 Vision Tool Reference
32. image we can see that it consists of different levels of intensity The Spectrograph Vision Tool is an area Vision Tool that is only available as a rectangle SID C 1 WarkPlate003 bmp DE x Pixel Graph DarkPlates Pro DER Pixel Intensity Position Along Graph Figure 54 I mage obtained with a DVT Spectral Sensor and pixel graph of the Spectrograph Vision Tool The functionality of the Vision Tool is shown in Figure 55 The squares represent the pixels and the text inside them represents the intensity level 88 o x lt tv 99 o ep i74 i75 i84 i85 Spectral Axis Figure 55 Pixel grid with intensity levels and Spectrograph Vision Tool interpreting the data Pixels are arranged in matrix style so we use matrix naming convention The intensity level at the pixel with coordinates 1 1 is given by i11 the one for the pixel with coordinates 3 5 is given by i35 and so on The Vision Tool is represented by the dark rectangle inside the pixel grid In this case the Vision Tool extends from pixel 3 2 to pixel 6 7 From the data inside this rectangle the Vision Tool must compute a spectrum In order to compute a spectrum the Vision Tool must use only one data point for every wavelength and since the X axis is the spectral axis it must use one single data point from every column of pixels inside the Vision Tool the Vision Tool
33. images When a number of iterations are selected to correct that effect the edge is correctly located However the data points caused by the noise are still active so the Vision Tool reports a straightness of 49 pixels When the outlier distance is used to discard points located more than 5 pixels away from the line the data points produced by the noise are discarded and the straightness drops down to 1 92 pixels This type of pass fail condition could be used to verify the quality of a cut or a drilling in a part Another use for the Measurement Vision Tools is positioning Even though Intellect has a dedicated number of Vision Tools for position reference Measurement Vision Tools can provide a position reference as well In cases where the positioning of a part needs to be very precise the user can select a Measurement Vision Tool instead of a Positioning Vision Tool as the position reference Math Operations Points and Lines Statistics Vision Tools Common math operations are performed on Vision Tool results by the Measure with Points and Lines Vision Tool and Statistics Vision Tool The Measure with Points and Lines Vision Tools offers an assortment of Vision Tools Unlike any other tools except Scripts these Vision Tools require no additional drawings These Vision Tools reference other Vision Tools that have been previously defined in the Inspection Usually they reference Measurement or other Math Vision Tools using their outputs lines
34. increasing the sigma factor The volume increases in all directions At this time the color Vision Tool recognizes any color inside the new volume as the learned color This makes the color selection more relaxed If the user wanted to make it more specific the sigma factor should be decreased to reduce the size of the original volume White 2 White Black Black White White Green Black Blue R a a Green PD Black Figure 50 Three dimensional illustration of the effect of the color Vision Tool parameters The first image shows the learned color the second one the effect of increasing the sigma factor The third one shows the effect of selecting the matte areas both for darker and brighter shades of the color The last image shows the effect of selecting the highlight areas 84 The third diagram lower left corner shows the effect of using the matte areas The volume is expanded towards black coordinates 0 0 0 to pick up darker shades of the color or away from black to pick up brighter shades of the color The user can select how much to extend the volume and in which direction darker brighter or both Finally the last diagram illustrates the use of highlight areas This option is intended to include shades of the color that are caused by surface reflections Those shades are between the original color and white which would be a full reflection of the light Increasing this factor expands the original
35. is best for this application o Integration questions Has anyone gotten the Vision Sensor amp a XYZ PLC to communicate For information on SmartList visit the DVT web site http www dvtsensors com and click Support Users can join the SmartList by visiting the support section of the DVTSensors website Cognex Certified Automation Solution Provider ASP Cognex sells DVT products through a worldwide network of Automation Solution Providers These ASPs are certified annually based on in depth knowledge of both Intellect and the DVT Vision Sensor If you are unsure of who is your Cognex Solution Provider you can search for that information on the Cognex website Please contact your local ASP with your technical support questions Stay informed about New Intellect Releases Visit the DVTSensors Web site for up to date information about forthcoming releases of Intellect There are two easy ways to reach the web site o From Intellect click on the Help menu and choose DVT on the Internet o Start your web browser and type http www dvtsensors com on the address bar 25 Chapter 2 A Closer Look at the System This chapter describes all the basic principles behind DVT Vision Sensors The internal structure of the Vision Sensor is described and a brief description about the parameters available at every level is provided From system level unique to every Vision Sensor to Vision Tool level dependent upon the Vision Tool being
36. is the case some regions of artificially high intensity levels may appear due to certain characteristics of the CCD To compensate for this occurrence Dark Image Subtraction may be applied by covering the lens with a lens cap and pressing Calibrate This calibration can then be used in the Spectrograph Vision Tool by selecting the option Subtract Black Image This will eliminate the aforementioned unwanted effect by subtracting the learned black image from the live region of interest of the Vision Tool This process does not affect the original image since it is applied just for the processing of a particular Vision Tool Dark Image Subtraction functionality can also be used to subtract two images from each other In these cases the learned image does not need to be dark In the Subtract Dark Image filter uncheck Truncate Negative Values to get the absolute value difference between two images Sensor Gain The sensor gain adjustment makes your Vision Sensor s CCD more sensitive to light Gain has a maximum value of 25 and is initially set to 2 A Gain of approximately 2 generally works best for the Vision Sensor 33 Hint Is your application on a constantly moving conveyor line Effective use of the gain setting allows you to minimize blur in your images due to relatively long exposure times With parts moving past the sensor increase the gain then decrease the exposure time until the images no longer appears blurry
37. need of training all the characters again After training the characters the user needs to establish the acceptance threshold that the characters being read need to match in order to be identified as one of the learned characters When the Vision Tool has successfully learned a character or matched it to a learned one the bounding box around the character changes from red to green The user needs to specify a matching threshold that dictates the percentage of similarity that the characters need to have to be considered the same character For sharp images with even illumination and very distinct characters a high percentage could be set As the image quality decreases or variation between similar characters increases due to a poor printing process the matching threshold must be reduced In cases where some characters tend to be deformed but still need to be read the ones that do not match the learned model should be trained as new characters In such cases the font list will increase for the Vision Tool will learn many instances of every character for example 4 different uppercase A s As the font list gets longer the processing time for this Vision Tool increases due to the increased number of comparisons that it has to make In order to overcome that increase in processing time the Vision Tool offers two options changes in resolution and auto fielding The Vision Tool has three different resolution levels high medium and low They differ f
38. of the written documentation are included e HTML Help The help file is a great source of information about all aspects of Intellect There are several ways to access the help file o Click on the Help menu and choose Help File Index or press F1 o Use the Help buttons located in most dialog boxes navigates to the relevant location in the help file o Hold the Shift key and press the F1 key to get the prompt From this click on any part of the user interface for context sensitive help o The Help file can be viewed independent of a Intellect session Simply click on the Windows Start menu choose DVT Applications and then choose Intellect Help o Access them directly from the DVT website These help files are continuously updated by DVT e PDF Files The written documentation provided by DVT in PDF format includes this Installation amp User Guide In addition the DVT Script Reference Manual is both loaded on your computer and available on line in PDF format A hard copy of the Script Reference can also be purchased separately through a DVT Distributor e Intellect Seminars Workshops Cognex offers Camera products through a worldwide network of Automation Solution Providers ASPs Local seminars and workshops can be found on the DVT website You can find this information on the web under the Education portion of the DVT website Also you can contact your local ASP for dates and locations of the next Intellect Seminar Workshop
39. of this Vision Tool is the set of available shapes The OCR Vision Tool comes in three different shapes rectangle parallelogram and arc The rectangle is used for text in standard position The parallelogram is used for text that is inclined like italics or text written at an angle The arc is for text that follows a circular arc Figure 47 shows four cases where the different shapes are being used READ ITALICS peer ExT AT AN ANGLE TEXT Ly Figure 47 Uses of the different shapes of OCR Vision Tool The top line uses a rectangle the second and third lines use a parallelogram and the last line uses an arc As the image shows besides reading the letters in many positions the Vision Tool offers image marking that straightens the text so the user can read it as well 80 After the Vision Tool is drawn and the threshold is set the user needs to isolate every character That is every character must have a red bounding box around it When that is not the case the user can change the extraction parameters which limit the size of the characters in width and height filter the image to eliminate noise eliminate stray pixels etc The extraction section of the Vision Tool is a combination of very powerful processing options As the user adds options the processing time for the Vision Tool will increase so a general rule is to improve the image as much as possible to make the inspection more reliable and to minimiz
40. on the right see diagram includes I O strobe and power screw down terminals The I O lines on this port are to be used when isolation is not needed The second port the one on the left side see diagram has the I O connections to be used in conjunction with isolation modules These terminals are inactive unless isolation modules are used Users should decide which lines need isolation and install the corresponding modules input or output for those lines only For more information refer to the following document on the DVT website DVT Isolation Break Out Board Note 22 Apply power to the Vision Sensor and wait for the system to boot The Status light will illuminate with a blinking green light when the boot sequence is finished The blinking green light will always blink when the camera is running and will increase the blink rate as the load increases Attach a lens to your Vision Sensor If you are using a C mount lens you will find it necessary to use a 5mm adapter LDS C If you have a CS mount lens you will not need the adapter 23 Getting More From I ntellect In addition to the Installation and User s Guide you can learn more about Intellect software from the following resources On line Documentation amp Help Files After Intellect Software has been installed on a PC all the necessary documentation is included along with the application software HTML Help and PDF Portable Document Format versions
41. or because it could not read anything low Script Outputs Script Outputs 1 16 that can be set through Scripts See the DVT Script Reference Manual for more details Unlike for input functions in addition to assigning specific functions to the I O pins the user can specify the polarity of an input Any line configured as an output on a Vision Sensor system is active in the high state The Invert Polarity option makes it active in the low state Other Communications Settings There are several ways to get data into and out of Vision Sensors including Ethernet and serial communications For specific information on these methods see Chapter 5 DVT Vision Sensor Integration Background Scripts Background Scripts are system wide programs that can run independent of the Inspection Product Some tasks assigned to Background Scripts are Product selection for an inspection register reading and writing exposure time control communications etc To get more information on Background Scripts consult the DVT Script Reference Manual available from DVT under the part number DOC SCR or from the DVT website for free download as part of the Intellect Software Power on Product The Power on Product allows the system to begin running inspections as soon as the Vision Sensor is turned on and alive Only Products that have been saved to flash memory may be assigned as Power on Products because those that are only in RAM memory will
42. set manually the user indicates which type of code is to be read or automatically sets the type of barcode upon read of the first instance of the barcode Usually applications need to read a certain type code which does not change 76 what changes the encoded message that the Vision Tool needs to be read Therefore the usual setup for this Vision Tool is to set the barcode type upon read auto detect if the user expects one of the seven types mentioned above otherwise the type should be specified Figure 43 shows sample barcodes PDF417 is the one on the left it can be observed that it is a very different type of barcode it is a stacked barcode When this is the case the Vision Tool creates more scanning lines to read the different levels of the stacked barcode Figure 43 Comparison of PDF417 Code 39 and PharmaCode types The first one is a stacked barcode type The last two barcodes in the image are Code 39 and PharmaCode For most users it is impossible to visually determine the type of code being used because they have very similar appearance In such cases the user should rely on the Vision Tool to determine the type 14141 Il Figure 44 UPC A Composite Code There are also composite codes see Figure 44 which consist of a 1 D and a stacked PDF417 or MicroPDF417 code The 1D portion could be any of the following UPC A EAN 13 EAN 8 UPC E USS 128 RSS 14 RSS 14 Truncated RSS 14 Stacked RSS 14 Sta
43. setting the parameters The parameters include the minimum number of pixels that each color must have to be included in the list Cluster Size and the maximum number of colors to learn from the part Maximum Cluster Count Based on those parameters the image is tested to get image marking showing which colors are learned Only after the desired colors are marked should the user learn the colors Since this method learns multiple colors at the same time the list of learned colors replaces any colors previously learned For more information about color parameters see Pixel Counting Vision Tool Color Vision Tool Dealing with Part Movement In real world applications parts to be inspected are not consistently placed in the same position for every inspection There are many parameters that affect this such as the use of proximity switches to indicate 93 presence absence of the part Those switches will only tell whether the part is present or not For more precise information about the location of the part proximity switches are not very reliable Intellect offers a number of tools to help the user locate the part in the image and to create a reference that the inspection Vision Tools can use to track the movement of the part This set of tools consists mainly of Vision Tools in the Positioning group however Vision Tools in the Measurement and Counting Groups can also be used for positioning These Vision Tools are used to calculate part movement
44. shows the functionality of this hardware device It consists of two stages of image acquisition Stage 1 is a regular lens that has to be used to correctly focus on the part The focusing lens can be removed for applications where the camera is inspecting a single color within the FOV Stage 2 consists of another optical device that takes a vertical line from the image focused by the lens and spreads the spectrum of that line over the CCD When this image is projected onto the CCD it consists of a grayscale image with no defined shapes in it That is because the spectrum consists of different levels of intensity at different locations in the image The X axis of the image becomes the Spectral axis that is if the external optical device is correctly placed blue tones should be on the low X coordinates and red tones should be on the high X coordinates Likewise the Y axis represents the Spatial axis This axis is the same as for a regular image but applied to a very narrow opening In other words a change in X coordinates would represent a change in wavelength whereas a change in Y coordinates would represent a change in position Object Focusing Optical Device Lens gt Figure 53 Functionality of the DVT Spectral Sensor Spatial Axis LA Spectral Axis Figure 54 shows an image obtained with the DVT Spectral Sensor and the pixel graph that the Spectrograph Vision Tool obtains from it As we analyze the
45. the Vision Tools that help the user set a threshold There are three types of image graphs Pixel Graph Histogram and Gradient Graph The Pixel Graph is the simplest way of displaying information about a Vision Tool path It uses the Vision Tool path as the x axis and the intensity of the pixels as the y axis That is the range displayed in the X axis goes from the origin to the end of the line Vision Tool whereas the range in the Y axis goes from zero intensity black to 100 white Figure 22 shows the pixel graph for a Vision Tool with a length of 408 pixels 45 Result Table Product2 Pixel Graph Show Graph Pital ntenalty Fonton Wong Graph Piel Figure 22 Example of a Pixel Graph for a line Vision Tool of 408 pixels in length As the graph illustrates the pixels near the center of the Vision Tool are dark low intensities then a light region is found so the graph peaks up to the high intensities and then it goes back down towards the low intensities as it approaches the end of the Vision Tool This occurs on each side of the center Histograms are also used to display the intensity of the pixels but in bar chart format Unlike pixel graphs histograms use the intensity levels ranging from 0 to 100 as the abscissa for the ordinate they use the percent pixels That is histograms display the percentage of the pixels found at every intensity level Figure 23 shows a histogram for an intensity Vision Tool The h
46. the maximum and minimum inspection times This graph should be used when two or more different methods for inspections are being tested Usually the time it takes to perform an inspection is crucial so after setting up different Vision Tools to perform a certain inspection this graph will tell the user which method is the fastest one Figure 14 shows a screen capture of this type of graph The information displayed in this graph can also be found in the Result Table and in the Properties Window of the Product z History Sweep Max Insp Time Mean Insp Time a Mean Btwn Insp Min Insp Time Figure 14 I nspection Times graph Finally the digital I O graph works like an oscilloscope It uses time as the abscissa X axis and eight configurable I O lines as the ordinate Y axis to show a timing diagram that indicates when signals go active or inactive This graph is very useful for troubleshooting communications Figure 15 shows a Digital I O graph 39 Digital 1 0 T8 Ph 8 Tr Ph T Ph TS Ph 5 TE Ph 4 TS Ph 3 TZ Ph2 TEPh 4 Figure 15 Digital I O graph The X axis indicates time in milliseconds Product Graphs Product graphs help users troubleshoot products as well as gather statistical data about the inspections The graph available at the Product level is the Pass Fail Graph The Result Table also displays product information and is available under the View menu These features are part of the Intellect
47. the tool as drawn Thus when this tool is used to track the rotation of a part the closer the center of the tool is to the true center of rotation of the part the more accurate the results Figure shows an example where the incorrect placement of the rotation tool causes a problem with the inspection In the upper left image we see an intensity tool at the tip of an arrow Since the center of the arc does not coincide with the center of rotation of the arrow as the arrow changes position the arc tracks it incorrectly It finds it but it uses its own center as the center of rotation In the third image the arc is correctly placed so as the arrow changes position the arc tracks it correctly and it passes a good reference for the intensity Vision Tool which performs the inspection at the tip of the arrow as expected 20 20 a5 25 as 25 10 30 10 30 5 35 5 35 20 15 25 O 5 35 5 Figure 33 Incorrect and correct uses for a rotational arc The second Vision Tool which reports rotation is the Line Fit Vision Tool this is a rectangle based Vision Tool that can be rotated This Vision Tool is used when an object with straight edges is not fixed in orientation The Vision Tool fits a line along the straight edge and tracks the rotation of the line A comparison between the arc and the parallelogram Line Fit is shown in Figure 66 Rotation Rotation Find Edge in Circular Arc Parallelogram N
48. to noise Blob Object and Pattern Counting take more processing time but they offer a number of features to filter out noise In every case image contrast plays a very important role The objective of the physical setup of the application should be to maximize contrast between features to be inspected and the background Figure 61 shows an example where the use of a different lens correction of working distance and use of appropriate light source increases the contrast between the part and the background 95 Figure 61 Importance of physical setup of the application to maximize contrast between part and background The image on the bottom is a better image due to the higher contrast between part and background the absence of reflections no pixels are saturated and sharper Flaw Detection I nspections Flaw Detection inspections typically involve looking for a general flaw on the surface of a part where the location of the flaw is unknown Typical Vision Tools used for flaw detection are located in the Flaw Detection Vision Tool group however other Vision Tools can be used for inspecting for flaws The choice of Vision Tool depends on the application Defect Detection can be used if the part contains a certain pattern that can be learned and searched for in subsequent images This Vision Tool takes a lot of processing time and system memory since the Vision Tool needs to keep the learned model in memory Color Monitoring can be used wh
49. triggered very fast the user interface will only receive some images This is why the display is called sampled image display it only displays sample images from the Vision Sensor Besides the case of the Vision Sensor being busy with inspections other factors influence the number of images transferred to the user interface such as network traffic the types of hub being used the Ethernet card being used the speed of the processor in the PC and the type of images being transferred color high resolution etc The top bar of the Video Display shows a number called the Image ID which is an incremental number assigned to every image The Image ID is reset on power up This number should only be used to monitor the rate at which images are being transferred The Vision Tool toolbox is where all Vision Tools are available This toolbar represents a shortcut to most options available under the Vision Tool menu of Intellect If the user prefers to use the main menu the toolbar can be hidden to maximize the work area by deselecting the Toolbox option from the View menu or pressing the close button at the corner of the Toolbox The Result Panel is a combination of two elements that have been discussed in this chapter The result table and the Tool graph for the Vision Tool that is selected from the result table When a Vision Tool has focus in the Video Display the too will be highlighted in the result table and the Tool graph to the left of the re
50. user interface they do not reside in the Vision Sensor The Pass Fail graph keeps count of the inspection results It Shows the actual counts of Fail and Pass outputs as well as an indication of the percentage of the total inspections taken that those counts represent The graph shows the number of inspections as the abscissa X axis and the running percentages of inspection results as the ordinate Y axis Figure 16 shows a Pass Fail graph japan ai Percent History Sweep Pass Count Pass Figure 16 Sample Pass Fail graph The Result Table is a list of all the Vision Tools in the product It consists of many columns of which the most important are the name of the Vision Tool the result for that specific Vision Tool the Method or type of Vision Tool the Cause of Failure the Order in which the tools are processed and the Timing ms information for that tool Figure 17 shows a sample result table It indicates the product name in this case Scratch Detection and it shows the Vision Tools being used as well as their outputs 40 Result Table Product8 ax Histogram Show Graph Show All Tools 4 Include All in Table Name Output Timing ms Result Cause E inspection Trigger aji Image Acquisition 15 2 5 C2 Ez root Count 0 Total Blob Count 1 Co 29 3 PASS Z Inspection Res 44 5 PASS EX Communications i 1 1 F Intensity Level lt gt Figure 17 Result Table
51. volume towards white Figure 51 shows an example of the use of the sigma factor The color Vision Tool learns only the light orange on the left end The search region is over all the colors and image marking shows where the color is identified For the example on the top row it happens to be only over the learned color This example uses a sigma factor of two For the second example the sigma factor was doubled For a sigma factor of four it identifies other colors as well The last two examples represent sigma factors of seven and ten respectively The Vision Tool is able to pick up different colors colors that do not reside inside the original matte line but as the sigma factor is expanded those other colors are included in the volume that identifies the learned color Figure 51 Illustration of the use of sigma factor to include other colors in the selection This Vision Tool can learn colors one by one This procedure can be repeated to learn as many colors as necessary The Vision Tool will keep a list of all the learned colors on the Manager tab There is another way to learn colors The capabilities are under the Multi Color section in the Training tab There are three choices Learn a Merged Color Remove and Add Through the first option the user can learn a group of colors and merge them together all in one operation The multiple remove and add operations will act on a group of colors previously learned and merged The r
52. your objective of clearing the contents of permanent memory COGNEX 119 10 Before proceeding make sure that the option Enable Reformat Flash on Firmware Download is enabled in Intellect You could verify this by closing the PC Communications dialog box and clicking on Options under the Edit menu in Intellect The option is indicated in the next figure System Connecting Disconnecting International lt Allow Multiple Ul Connections Auto Connect at Startup Start Playing Video when Connecting Open Result Table when Connecting Open Toolbox Window when Connecting SI S S Es Close Network Window when Connecting Close Emulator When Disconnecting Without Asking E Ask to Backup System When Disconnecting iscellaneous able Reformat Flash on Firmware Dewhload Synchronize Inspected and Selected Products v Auto Name Products and Sensors v Show Beta Warning at Startup vanced C Enable Dragging and Dropping Docked Windows _ Enable Access Control 11 On the Network Explorer window select the DVT Vision Sensor on the list and right mouse button click and select the Load Firmware menu Select the firmware version that you want to load based on your model The firmware files for all the systems are included in the Intellect installation and their extensions identify the sensors for which they were designed At this point
53. 05 Legend 510 540310918 Smart Camera Intellect Version 1 2 0 ALPHA 5 Testing Legend 540 540311569 Smart Camera Intellect Version 1 2 0 ALPHA 5 Testing Legend 540 542310681 Smart Camera Intellect Version 1 2 0 Beta 4 Build 29062005 Legend 542C 542410206 Smart Camera Intellect Version 1 2 0 ALPHA 5 Testing Legend 542C SmartImage Se Legend 540 Diagnostics 1 4 0 Build 28042005 Legend 542C 544510399 SmartImage Se Framework Version 2 7 5 Build 23032005 Legend 544 544610625 Smart Camera Intellect Version 1 2 0 ALPHA 5 Testing Legend 544 544810141 Smart Camera Intellect Version 1 1 4 ALPHA 11 Bead Track Legend 544C 550220002 Smart Camera Intellect Version 1 2 0 ALPHA 5 Testing Legend 550 550220012 Smart Camera Intellect Version 1 1 1 Build 30032005 Legend 550 550220034 Smart Camera Intellect Version 1 2 0 Beta 4 Build 29062005 Legend 550 9 If this version is 0 28 or a more recent release like in the case above you would be able to erase flash memory and load the new firmware version from Intellect If your system has an older diagnostics version go to the section Erasing flash using Telnet at the end of this appendix and then continue on step 11 The mentioned section explains a fail safe method to erase flash memory so if your system has a recent diagnostics version but the procedure described below to accomplish this task does not work you can still refer to the technique covered at the end of the appendix to achieve
54. 5 PharmaCode UPC EAN Code 93 RSS 14 POSTNET Snowflake 2D code and DataMatrix codes ECC200 and older It can also perform 1D barcode grading Optical Character Recognition and Optical Character Verification OCV This vision sensor shares the form factor of the Legend 500 Series of vision sensors The DVT Spectral Sensor This Vision Sensor uses a grayscale CCD with resolution of 640 by 480 and an external spectrograph It is a spectral line imaging Vision Sensor The DVT Spectral Sensor captures a line image of a target using prisms and grating optics it disperses light from the line image along the spectrum Each captured image contains line pixels in spatial axis Y axis and spectral pixels in spectral axis X axis Unlike other color smart cameras using RGB platforms the DVT Spectral Sensor offers more detailed color information across the entire visible and Near Infrared NIR spectrum This allows the CCD to capture more data for more accurate measurements and detection of very slight color variations Unlike point color spectrophotometers the DVT Spectral Camera provides spatial resolution and simultaneous measurement across a large number of points Figure 2 shows the DVT Spectral Sensor It shares has the same form factor as the other DVT Vision Sensors but it requires a different piece of hardware to visualize the spectrum of the part being inspected It should be noted that the DVT Spectral Sensor does not come with the integrated
55. 5 0 0 255 255 0 0 255 255 0 0 255 255 248 0 255 255 0 0 255 255 0 0 make sure the IP address and subnet mask are compatible with your computer s IP address and subnet mask If you need to change the IP address and or the subnet mask of the DVT Vision Sensor select the appropriate file for the Vision Sensor Properties window and change the IP address and subnet values Properties 5f E Y actions DER 2 Camera DYT Smart Camera Properties 3 General Properties Name Group MAC Address Serial Number Network Settings IP Address IP Mask Default Gateway Eth Link Speed Duplex Settings Camera Type Model Application Feedback Status DYT Smart Camera 00 90 68 01 01 cF 53025133 192 168 2 107 255 255 0 0 0 0 0 0 Auto Smart Camera Legend 530 Intellect Version 1 1 1 Build Up 5 It is recommended that before loading firmware into the system the user erases the content of flash memory This will avoid potential problems that could arise when loading different firmware versions on top of one another The first step to do this is forcing the system into diagnostics mode Select the appropriate DVT Vision Sensor under Network Neighborhood by right mouse button clicking and selecting Force Diagnostics Intellect will instruct you to cycle power on the system you are trying to upgrade COGNEX 118 Force Diagnostics Please cycle power on your Smartlmage Sensor If this di
56. 7 determine that the length of the Vision Tool is about 60 pixels and that the edge transition from bright to dark is located close to pixel number 32 The output of this type of Vision Tool is the number of edges found in this case it is one However the user must be careful to select the correct type of edge to be located If in this case the user had selected dark to bright edges only the Tool would have returned zero edges because there are no such edges in the direction of scanning Count along a Line Vision Tools are available only as line Vision Tools because of their purpose Since they detect edges they must consist of lines searching for transitions between dark and bright pixels along a certain path As a consequence a single dark pixel like background noise could make them find extra edges and thus alter the result of the inspection This type of Vision Tool can be set to pass or fail based on maximum edge count minimum edge count finding the appropriate number of edges and minimum contrast to find edges FeatureCounting Count along a Line Vision Tools The Count along a Line Vision Tool in Feature Counting mode is designed to detect and count features that make the part being inspected different from the background A feature as interpreted by Intellect is defined by two consecutive opposite edges For example a transition from bright to dark followed by a transition from dark to bright indicates the presence of a dark ob
57. AS NN 3 Chapter 1 Gettine Started Quan nn as 9 What is Machine CI mem aaa A un ese ssssssssssaeeysssssssee 10 Imaging and Pixels ise eee anu Ure date prn m eee ms 10 What is a DVT Vision Sensor 10 DVT Vision Sensors Product Family eese tirintas iieii aniei nre trennen ennt ennt enne 10 Installing Intellect Software 16 Connecting to the DVT Vision Sensor e eere ee ee ee ees an esso sese ta sete to sepan ee eoa seen s sese pases eaae ts 16 DVT Vision Sensor Hardware Setup 21 Unpacking and Powering the DVT Vision Sensor esee enne ener treten tree 21 Chapter 2 A Closer Look at the System 27 System Parameter S A TON 29 Inspection Modera s sc E deh eno ec ete teo ens 29 Password Protection ti A DR one pua 29 Digital VO Configuration scien adi 30 Other Communications Settings 3 aboard n Ot OC DP Anant ee tiie ahaa 32 B ck round SCEIpts iioii onere er e i rie lada 32 Power On Product sve 4 2 e to rt c eo ge D eee t hr RE IRI cubes E Ree ye e EEKE ES 32 Trigger Sources sebbene peel dele Sene
58. Aggregate operation can be used to concatenate the operations with one Vision Tool Morphology Performs dilation erosion open or close operations to help eliminate small holes in an image to remove small noise pixels Noise Reduction Smoothens the image by performing low pass or median operations Effective at reducing small noise pixels however it also causes a blurring effect Gradient High pass filter type operations highlight edges that are sharp in the image This can be useful when the edges are sharp but the lighting is non uniform Thresholding The Thresholding filter is used to suppress areas of the image based on the filter criteria by turning them to a black intensity so that they can be ignored The Color filter allows a specific color or colors to be eliminated and set to black or for the background to be suppressed to black The Edge filter will eliminate edges by setting the edge pixels to a background black color The Blob Filter allows connected regions of pixels to be ignored or passed through Segmentation sets edge pixels to black background and finds segments enclosed by edge pixels 69 Enhancement The Enhance filter group accentuates the image by providing different effects like extending the dynamic range of the intensities darkening the edges suppressing or enhancing color planes etc FOV Balance Used to compensate for consistent non uniform lighting Used most commonly for Reader a
59. ETC ccccccsssscssscssssecssccsssceeseecssssecsaecssssecseeseasecseseseasecsaseseaeecsseseaaecesessaaeen 104 Industrial Protocols er A ee ERE ARM E re EORR Ee M RR Eee EE 105 VDX rhe reta ea Ata ae ent tet ihe atem entente iier 105 Appendix A Emulator tutorial 107 Appendix B Basic TCP IP Setup 109 Appendix LC Advanced TOP L u Suasana Dam uqapas POUR EUNT aw aula kas di 113 TCP IP Installation Lips I a Rm 113 TCP IP Troubleshooting Tips 114 Ee vili m 115 Appendix D Upgrading or Reinstalling DVT Vision Sensor Firmwatre 117 To back up a DVT Vision Sensor system to a PC 117 To install Intellect on a PC 1 eres S Squash G qua aG awasi noo setae tasa siss 117 Upgrading Intellect firmware on a DVT Vision Sensor 117 Erasing flash Using Telhet E M 120 Appendix E Breakout Boards 121 Isolation Breakout Board cerei ee
60. Gray corresponds to blobs that are being counted Boundary blobs blobs that touch the edges of the Vision Tool have no marking In the case of the boundary blobs the user selects whether those blobs should be counted or discarded If the option is to count them they will be marked in gray just like regular blobs Blobs that have been discarded because of their size will have no marking The Selection parameters are used to isolate blobs created in the generation phase The main use of this tab is to help the user find the blob s that the application requires by calculating a number of parameters about the blobs s If the objective is to track a part for rotation and translation a particular blob must be isolated and its position must be calculated When this is done other Vision Tools can reference the blob selector for position reference If the objective is simply to count the blobs or to verify their correct size shape the Vision Tool can do that automatically The parameters that the Vision Tool can extract from every blob are angle position area bounding box size eccentricity compactness perimeter average intensity and radius For an explanation of these parameters see Error Reference source not found at the end of this section The user can choose to use some or all of these parameters to help discriminate between the desired blobs and other blobs in the image A match score is generated based on a combination of all the selected blo
61. IP address to use When the camera is not in diagnostics mode the user can select a Vision Sensor and enter an IP Address for the Vision Sensor in the Properties Window that appears when the Vision Sensor is selected Please use the following steps to set up your computer and DVT Vision Sensor with the correct IP addresses e Start Intellect e The Network Window will open automatically at startup See Figure 5 17 m E Ea GE Commands y P EE A J C Emulators 6 E Network Neighborhood Ethernet Favorites Network Emulators Adapters Neighborhood Ethernet Adapters Figure 5 Network Explorer Window e Click and Open the Ethernet Adapters folder This will show you the current Ethernet Devices that your PC has available and their properties Record your computer s Host IP Address and IP Mask on a piece of paper You will need to set the Vision Sensors address to be compatible to your PC s address e Click on Network Neighborhood See Figure 6 e Network Neighborhood allows you to identify DVT Vision Sensors on a network Your computer will search your local network for Vision Sensors If no sensors are found wait about 10 seconds and search again There is sometimes a small delay due to the time it takes for your computer to recognize the Vision Sensor er nerugrieEzlorer x El actos nmam 9 Name Status Group IP Address IP Mask MAC Address Serial Camera T Application Model amp 3 Net
62. OCR Vision Tool to locate the first character and another Vision Tool to read the code This option of finding the first character makes the positioning very independent of noise since the Vision Tool will be looking for a specific learned character not an edge or a feature 1D Reader The 1D Reader Vision Tool consists of two line based tools arc and straight and an area based Vision Tool The line based versions of the Vision Tool scan along a line trying to read a certain bar code The user has a few options to speed up the process or to make it very thorough When the application consists of the same type of code every time the user can set the Vision Tool to look for that specific code This will reduce the processing time because the Vision Tool does not need to attempt to decode the data using other methods When the application determines that different types of barcode are to be used the user must select the option to remain in auto detect In this case the Vision Tool not only reads the code but it also determines what type of code it is This option requires more processing time The parallelogram version of the 1D Reader Vision Tool will help in cases where the position of the code changes from image to image handling translation and some amount of rotation 2D Reader There DataMatrix reader is a searching Vision Tool The DataMatrix Vision Tool searches for the code in a predefined area Even if the code rotates the Vision
63. Readers E A 76 1D Barcode Reader uuu saa qampaqa E 76 2D R eade f1i ua OT 78 COGNEX 125 oro y eh ne Sees 66 Script Debug WindOW ccccssseeeeeseseeeeennaeeeeeennaeeeeeonaeesenaaeeeeeoeaseesenoaseasenonaseeeeonaseesenoaseeeoaaeeneaey 49 A AAPP A 33 Sensor GraphS u uN TN 45 Jolqd co m 88 Spectrum Calibration Q nnmnnn nn Q Q 34 Stati SUCS PO00PPPCOOOOOC O0O0OO O O0UO IN 74 System Parameters J J J J Q Q J J 29 Background Scripts esti sri ingin anatina dao 32 49 Dark Image Subtraction ua s paui dadas 33 Digital I O configuation ua cile etat rrr re den e nre a Ea 30 FOV Balance M HQ 33 TAPUESFUNCTIONS y saus 30 Inspection Mode s kum mun ee E Ret re nu u Im tana aaa manu iii 29 Inspection Mod aii A A A crea A bien aaa av de 50 Output FUNCION tee add 31 Power on uror i oo asas 32 Reflectance Calibre 34 Spectrum Calibration eere tete EE i 34 Heer MELLE 33 White Image Normalization u uuu Seit tea sine ia DEDE quspaqa asua ss 33 System Specifications 12 Template Matching e UU I UU ee sese asus
64. Result Table Pr AAR 2 2 l z gt a u P x Powton Nong Gras Posa Figure 37 Effect of the use of the best edge option The Vision Tool on the left fails to locate the edge because of the background noise whereas the one on the right looks for the best edge the highest peak in the gradient graph All these options increase the processing time of the inspection so if timing is an important issue the user should first try to avoid them by changing the light or the lens being used to improve the image If sub pixel accuracy is not a requirement the Vision Tools can use intensity based thresholds This option may increase repeatability in the measurement and it adds some advanced options to deal with noisy images as well For more information on these operations see Processing Operations under Vision Tool Parameters Besides the specific parameters discussed so far some measurement tools include extra options to make the Vision Tool more precise When area based Measurement Vision Tools are being used more parameters become available Scan Density Max Iterations and Outlier Distance e The Max Iterations option lets the user indicate how many times to recalculate the line circle being interpolated using the data points After every calculation points are assigned a certain weight for the next calculation based on the distance from them to the computed output line circle By doing this the algorithm
65. The Vision Tool in this case is detecting the label presence on the computer disk This particular example uses a thin rectangular search area to limit the inspection area The pixels within this area are grouped based on their intensity levels The histograms illustrate the pixel analysis of the image For the first case the label is present so most pixels under the Vision Tool are light This is reflected in the histogram which shows about ninety percent of the area above the minimum threshold and below the maximum threshold values For the second case all the pixels are dark below the minimum threshold so the Vision Tool reports 0 This example only required the verification that the label reached a certain point so the thin search area Vision Tool was adequate but if the inspection consisted of the verification of the entire label a larger rectangular area Vision Tool could be been drawn over the label This type of Vision Tool can be set to pass or fail based on the of pixels matching the threshold criteria or learned colors For the example above a minimum Pixel count should be established to determine what is acceptable and what is not A minimum bright area of 90 would cause the Vision Tool to pass when the label is correctly placed and to fail when the label is incorrectly placed Blob Counting Count in Area Vision Tools The Count in Area Vision Tool in Blob Counting mode is designed to find count or track blobs Blobs in Inte
66. Tool will find it and read it This option takes more processing time because the Vision Tool needs to search for the code in what usually is a noisy image typically the code is surrounded by text In order to speed up the process the user should provide the Vision Tool with as many parameters as possible about the type of code to search for so the searching process is faster The SnowFlake reader in Intellect has a rectangular shape and is a searching reader 99 Chapter 5 DVT Vision Sensor I ntegration This chapter discusses the different ways in which the user can send data to the DVT Vision Sensor or get data out of it The most common method is with the digital I O lines which were described under System Parameters This chapter explains how to implement Modbus transfers how to set up DataLink how to set up the built in drivers and how to enable disable different operational modes It also mentions the types of communications that DVT Vision Sensors support 101 Transferring Data from a DVT Vision Sensor The most important factor to consider before setting up a data transfer is the timing Information about an inspection needs to arrive in a certain way for the receiving system to interpret it correctly There are two ways to transfer data synchronous and asynchronous Synchronous transfers of data happen after every inspection The user sets up the data to be transferred and that data is sent out after every inspection
67. Trigger was received while the system was acquiring another image Run Mode Output used to indicate the inspection running state of the system The output will be active when the system is set to running of inspections 31 Output used to indicate the inspection running mode of the system The output will be Trigger Mode active when the system is set to external trigger and inactive when system is set to internal trigger Trigger Ack Signal that goes active when the input trigger is detected Select Pass While Select input is active Select Pass signals that the Product ID bits specified a Product ID found in the system While Select input is active Select Fail signals that the Product I D bits specified an Select Fail Hagar invalid Product ID Signaled after Inspection Trigger is read during exposure time and image Acquiring digitization Another Inspection Trigger cannot be signaled while Acquiring is active Inspectin Signaled after the Acquiring signal while an image is being processed for inspection p 9 Note Acquiring Inspecting Busy 21 Changes state once after each inspection is performed oggle User1 User definable outputs that go active or inactive based on combination of the results of User16 the Vision Tools being used User Definable outputs are Product specific Wronq Code Indicates whether any reader Vision Tool in the product failed because of a string mismatch high
68. UU U uQ 64 Terminal Window 111 ueeeeeieieee ideada a suka wa ayasa ua aua RR Rua RAN RR SERRA RR RSERRR RR SERA ren Vsa Rn a Faan 49 Threshold P 43 Adaptive night inet ene iaa dv UP eeu as 44 A to Bimodal y u saa yau aa ii aia 44 Dominant Color lt uu S Qua aaa nasaq dh Quy 83 Fixed Vallina ta han rare ives ites tea an D PE ede aad ae 43 eir TIE ET 44 jo SASS ia O LE A Rau iu HIGHER OUEST 80 Percent f PathContrast n rere t Idi ERE enr abet aa e a HELD E XA EN Vara da Ead ee as 43 Percent of Reference Intensitles iier rennen in rna a xia d ca a ua da aen dna 44 Training araisa 24 Translation AAA 65 COGNEX 126 Trigger SoQWCe 33 l 1 3 4 70 Vision Sensor Product PA AMES y IRN A A a uN S ays 34 System Parameters c asini A A a aa ERR ayau 29 Vision Tool Parameters Digital Sis IEEE DIDIT 47 Image PROCESSING ie sass RR 42 ResuR A A A A dr 44 Sensor AA e a ia 45 MP A as io ada 41 TO a qaa 43 VISION TOOIS AA OO 55 Area POSIIONINO cocinas P R 67 A AN 83 Color MO ILOrI simi ES 86 Color Spate eT 83 Count Ai A da 60 63 64 EdgeCo0m08 des coco sana heo OEA ale tebe ERARIO Ia PESE riage LE CU DARET CARRIE AAA dani aati 57 A nuusan Shi suu b NT 58 Identification
69. User output For example if the positioning Vision Tool fails a certain string can be sent out but if this one passes DataLink could look at the result from another Vision Tool to determine which string if any to send out Once the conditions are indicated the strings need to be created This is a simple point and click process that gives the user access to data from every Vision Tool in the Product plus the possibility of typing some extra characters Figure 63 shows a screen capture of DataLink string editor String Expression Editor String Definition Tool Parameters The radius is Tool2 RadiusKcrAf E Cam2 Inspection Image amp amp Product amp B Tools Too 2 Tool2 Result ResultString Sample Display OutputS caleR atio The radius is 123 123457 Radius Fail Character v Place Holders Spaces Line Termination mE mre gt C Figure 63 String setup for DataLink 102 The last section of the string is the end of line character which is available from the menu shown in the lower right corner In this case cr If was selected which gives a carriage return followed by a line feed Depending on the output from every Vision Tool one of the selected messages Strings will be sent out or in some cases no string will be sent out ex if all the Vision Tools pass This will give the user the tools to determine where the flaw is in the process and allow him to take immediate action The fact
70. a Vision Tool requires more processing time because it not only consists of many scanning lines but it also requires further processing for the line fitting calculation One way to reduce the processing time is to reduce the scan density in the Shape Parameters page Note that if the Scan Direction is set to Inside Out and the center line of the Vision Tool is not inside the part it will fail The Measurement Vision Tools that calculate radii are the Measure in Circle They have the same functionality they differ only on their applications A Find Circle tool should be used when the circle to be measured is a complete circle The segmented version of this tool is used when there is not a full circle Figure 40 illustrates the use of these two different tools Point Center of best fit circle 73 Figure 40 Different uses of Find Circle and Segmented Find Circle tools To use these tools the user draws two circles one inside the part and one outside Then scanning lines will go from the first circle drawn towards the second one looking for the edges of the part The intersections of the scanning lines with the edge of the part determine data points The algorithm then fits a circle through those points Different outputs can be obtained from the area based tools The user can select minimum maximum median or average distance or radius depending on the tool being used These tools can be set to p
71. alog box does not close 30 seconds after power is reapplied to the Smartlmage Sensor press the Close button 6 After the system boots up it should be in diagnostics mode You can check this by verifying that the Status LED on the back of the Vision Sensor is blinking red Also under Network Neighborhood the system should appear now as DIAGNOSTICS 7 When the system is forced into diagnostics mode it resets its IP address This means that at this point you would need to select the system click on the Edit button and reassign the appropriate IP address and net mask 8 Now that the system is in diagnostics mode you can proceed to erase flash memory While the Vision Sensor is in diagnostics look in the Application Column of the Network Explorer table and identify the diagnostics version of the system 4 Network Explorer GE Actions E a o Network Explorer fialNu Camera Type Application E Network Neighborhood 53003247 Smart Camera Intellect Version 1 2 0 ALPHA 5 Testing Legend 530 Gard 53025133 Smart Camera Intellect Version 1 1 1 Build 30032005 Legend 530 a ae 500000100 IntelligentScanner Intellect Version 1 2 0 ALPHA 5 Testing Legend IS GB Favorites 510221361 Smart Camera Intellect Version 1 2 0 ALPHA 5 Testing Legend 510 Gq Ethernet Adapters 510221590 Smart Camera Intellect Version 1 1 3 Build 02062005 Legend 510 510221708 Smart Camera Intellect Version 1 1 3 Build 020620
72. and points for the calculations The Points and Lines Vision Tool calculates a distance or angle based on lines and points generated from other Vision Tools or it constructs new points or lines based on the references Table shows a list of these operations and indicates the type of reference that the Vision Tool needs and the output it produces 74 Table 8 Summary of math operations in the Points and Line Vision Tool Math Tool References Returns Distance Two points The distance between the reference points Two lines The distance between the reference lines The perpendicular distance from the reference A point and a line Angle point to the reference line Two lines The angle between the reference lines Intersection Two lines The coordinates of the intersection of the reference lines Midpoint Two points The coordinates of the midpoint between the p p reference points The coordinates of the midpoint between the A point and a line reference point and the reference line Midline A line parallel to the reference line through the A point and a line midpoint of the reference point and the reference line The bisector of the angle determined by the Two lines reference lines Line through two points Two points A line through the reference points I The perpendicular to the reference line through Perpendicular Line A point and a line the reference point Defect Dete
73. ap or jpeg images in the selected directory with the name and 3 digits indicating the image number The setup shown in the dialog box above would save the following images leftSide005 bmp leftSide006 bmp leftSide007 bmp leftSide008 bmp leftSide009 bmp and leftSide010 bmp in the C Temp directory This procedure saves every image that Intellect brings from the Vision Sensor In the Image Acquisition properties window the user can select which images to bring to the user interface If only the failed images are to be saved for example the user should select to display Failed Images only The Real Time Feedback should be started as usual from Intellect When the user wants to start recording the red circle Record button should be pressed from the image toolbar Step 3 Once the Product or System file and the images are available from the hard drive the user can start Intellect and connect to an Emulator The Emulator should be selected to match the Vision Sensor from which the images or Product System files originated Upon connection to the Emulator Intellect will show the SID and make the standard editing options available At this point the user can load the image sequence and the Product or System file In order to load the image sequence the user needs to select the option Configure Sequence under Images The following dialog box will appear COGNEX 107 Configure Sequence Image Sequence All Images in Directory Browse
74. ass or fail based on specifications for the distances being measured min radius max offset etc when the inspection consists of the determination of a correct size Another feature that the user can select for quality control is the overall roundness straightness Depending on the area tool being used there will be an extra output that indicates how spread out around the output line circle the data points are In other words straightness or roundness is given by the sum of the distances between the data point that is farthest away in one direction and the one farthest away in the other direction of the result line or circle Hence a perfect edge would produce a very small straightness roundness for a circle whereas a noisy edge would produce a high straightness roundness for a circle In this case the outlier distance helps a lot in presence of noise When noise produces data points for the final line the straightness can increase considerably That is one single data point caused by noise far from the edge will increase the straightness dramatically Outlier distance will discard those so the calculation for straightness concentrates on true edge data points instead of noise Figure 41 illustrates the use of this option The figure shows a dark part and a noisy background The dark pixels of the background cause some scan lines to identify data points far from the edge Figure 41 Effect of Outlier distance on Straightness for noisy
75. ause neighbor pixels mostly in the vertical direction to saturate even though their original intensity level was below saturation When Antiblooming is turned on local spots of overexposure are reduced thus minimizing streaks and washed out areas of the image Blooming is not an issue for the Legend 515 system because of light accumulation characteristics Antiblooming is always enabled for the 535 545 552C 554 and 554C systems Warning Do not enable Antiblooming when working with the Measurement Vision Tool when using sub pixel computations Results may be affected by as much as one full pixel when Antiblooming is activated Illumination The illumination signal is a digital output normally configured on pin 8 in a DVT Vision Sensor Strobe light sources from the DVT product with part numbers of the form IDxx are designed to use the strobe illumination signal see Figure 11 Figure 11 A strobe illumination source I DRA that uses the strobe output Pulse width for the strobe signal is determined by the Product exposure time which is a Product specific parameter These two controls are tied together so the strobe light remains on for the duration of the image sensor s exposure to light For DVT Vision Sensors this option of illumination enabled disabled controls the integrated LED ring as well This will allow the user to gain some control over illumination without using an I O line However when more specifi
76. averages the pixels in each column to obtain a single data point The DVT Spectral Camera will come calibrated in nanometers and the user can recalibrate at any time This means that peak reflection locations will be specified in this unit rather than just image coordinates The user can also perform binning operations in both the spectral and spatial axes Binning can be used in applications where the brightness has to be increased without increasing the exposure time Since the DVT Spectral Sensor will be calibrated it will be possible to compute absolute color data for different color spaces After a Dark Image Calibration is done the user can select the option to subtract the black image from the spectrum being analyzed by the Spectrograph Vision Tool The functionality of this Vision Tool is similar to that of color Vision Tools The user can learn different spectrums and compare the observed spectrum with the learned ones In order to maximize accuracy in the comparison the user can scale the spectrums to the peak values This Vision Tool can be set to pass or fail based on maximum spectrum difference maximum change in location of peak wavelength and maximum change in peak reflection using a learned spectrum for comparison 89 Chapter 4 Inspection Application Guidelines This chapter provides major guidelines to approach different inspections Users should be familiar with the different types of Vision Tools available in order to
77. b parameters The Vision Tool can display the value of the selected parameters for every blob in the image Note the user should use an Area Positioning Vision Tool if a part needs to be tracked and other Vision Tools will be repositioned based on the part location However if multiple position information is desired the Count in Area Vision Tool in combination with a script or datalink transfer can be used to output multiple position information to other devices Figure 30 shows an example where a particular type of part is being counted based on its distinct blob characteristics Four blobs are generated but only one meets the counting criteria Figure 30 Use of the blob selector for position reference As the figure shows only one blob is being selected highlighted in white The image also shows the marking for the orientation of the part the blue crosshair at the center of it This blue crosshair has a tail to indicate the angular orientation of the part Figure shows an example where blob tools are used for flaw detection and part counting The first image shows two pills The second image shows the image marking for the blob tool when both pills are found In this case the Vision Tool can be set to pass based on pill count 61 O Figure 31 Example of use of blob tools for flaw detection part counting The last image shows the marking for a case where one of the pills is defective The damaged pill is discarded
78. be lost on power down The Power on Product assignment is critical when the Vision Sensor is used as a stand alone system Once the system is configured with a PC the Power on Product must be assigned in order for the sensor to start running inspections thus signal digital outputs immediately after cycling the power When the system has any products saved in flash memory Intellect will be in Run mode In selecting the Power on Product at start up the Vision Sensor selects the named Product for inspections called the Current Inspection Product Note A Vision Sensor without a product saved to flash memory will not start running inspections after power up Trigger Source Another system parameter is the trigger source This parameter indicates how the system is triggered The options are external trigger and internal trigger External trigger requires that the trigger input function be assigned to an I O line and that an external device provide a signal on that input whenever an image is to be taken Internal trigger is an automatic mode in which the Vision Sensor takes a new image periodically at fixed user defined intervals or at an automatic rate LineScan systems have an extra mode for continuous mode acquisition used for web applications Note When working at full speed the Vision Sensor may show a slow response to communications because the inspections take priority over other processes When external trigger is the option for trig
79. bject and should be drawn just outside the object The outer area indicates the region to search for the object Object Locate Vision Tools have a number of parameters that the user can set to better find the objects In order to minimize processing time the user can limit the movement that the objects are to have That is when the application allows for it the user could limit the movement in the X and Y directions as well as rotation and scale so the search for the object does not take much processing time It is for these cases that the Vision Tool offers a scaling tolerance parameter which the user can select to identify objects when they are proportionally bigger or smaller than the learned model Another important parameter that Object Locate Vision Tools have is flexibility The user can set the Vision Tool to be more or less flexible The Vision Tool should be less flexible when the object to be located does not vary in size or geometry If the parts are neither defective nor overlapping the Vision Tool should only recognize the presence of an object when many features of the learned model are present in the area This option makes the Vision Tool less susceptible to noise For the opposite case when objects tend to overlap or even change in geometry the Vision Tool should be made more flexible This will allow the Vision Tool to find objects where there are only a few characteristics of the learned model The user should keep in mind that th
80. ble OCR Vision Tool is a fast process that can handle scaled and rotated characters Feature extraction is fully trainable which means even symbols foreign characters or mixed font sets can be read This is a very important feature the trainable OCR Vision Tool is not limited to OCR fonts which are fonts designed to be read by standard OCR readers This tool can be used to read anything the user only needs to train it first i e teach the Vision Tool what needs to be read In addition it can be trained on a sequence of characters so that it can be used as an OCV Vision Tool Instead of simply reading a code it can also verify that a certain code is present Unlike normal correlation it can handle any type of character marking such as dot matrix laser etching laser marking ink jet video jet dot peening etc The trainable OCR Vision Tool can be trained on any type of character with any type of font however some font styles work better than others Special OCR fonts have been developed to make reading 79 easier by making characters with the same width i e II and WW are II and ww and by making similar characters as different as possible i e 8 and B are amp and B Other factors that will help you achieve the most reliable and robust readings are e Achieve high contrast between the characters and the background e Make sure characters have good separation e Malntain a character height of between 20 and 35 pixels e Try to m
81. ble operations are e Erode shrinks shapes in the image a user specified number of pixels Useful operation when dealing with background noise e Dilate expands shapes in the image a user specified number of pixels Useful operation when dealing with noise inside the part e Open combination of Erode operation followed by Dilate operation This option eliminates background noise and does not alter the sizes of the parts e Close combination of Dilate operation followed by Erode operation This option eliminates noise inside the part and does not alter the sizes of the parts Figure 19 illustrates the use of the Erode and the Open operations In this case the dark part being analyzed is in presence of background noise 42 Figure 19 Noisy image illustrates use of Erode and Open operations The Vision Tool on the left uses neither the one in the center uses the Erode operation and the Vision Tool on the right uses the Open operation The use of a Vision Tool with no options of image processing would result in an inspection of the part and the noise as shown in the first Vision Tool The second Vision Tool uses the Erode operation it shrinks everything 3 pixels in this case until the noise is gone but that affects the original size of the part The third Vision Tool uses the Open operation that is after shrinking the parts it expands them The result is the noise disappearing and only the part to be inspected being expanded to its or
82. c lighting is needed up to three external strobe lights besides the integrated LED ring can be controlled using the digital I O lines 36 Product Identification Every product in a Vision is assigned a number called the Product Digital ID which is used to reference the product This number enables the user to send a digital signal to the Vision Sensor to indicate which product to use for a specific inspection In order to do that a number of I O lines must be dedicated to the Product ID bit input function The number of lines dedicated to this function determines the maximum number of products that can be selected externally Basically n lines dedicated to Product ID bits will enable the user to select among 2 products A common configuration for I O setup involves designating 4 lines as Product ID bits bits 0 through 3 The following table reviews the binary combinations for 16 Product ID numbers binary 0 15 using these 4 input bits Table 5 Product ID Bit Binary Patterns Binary Pattern Binary Pattern Product Binary Pattern Product ID ID Bit 3 Bit 2 Bit1 ProductID Bit 3 Bit 2 Bit 1 Bit 3 Bit 2 Bit 1 Bit O Bit 0 Bit 0 0 0 0 0 0 6 0 1 1 0 12 1 1 0 0 1 0 0 0 1 7 0 1 1 1 13 1 1 0 1 2 0 0 1 0 8 1 0 0 0 14 1 1 1 0 3 0 0 1 1 9 1 0 0 1 15 1 1 1 1 4 0 1 0 0 10 1 0 1 0 5 0 1 0 1 11 1 0 1 1 Product Selection Digitally selecting a Product is a simple process R
83. can be used by themselves to identify parts are Blob Locate Object Locate Color Pixel Counting Reader Pattern Locating Match Vision Tools Blob Vision Tools should be used when the parts can be identified based on general geometric features Area Radius Eccentricity Compactness etc When a more precise identification needs to be done Object Locate should be used at the expense of some extra processing time Pixel Counting Vision Tools should be used when the difference between parts is based on color Finally Reader Vision Tools should be used when the difference is in a barcode DataMatrix or a label with characters In those cases the user needs a Vision Tool to read the data from the label or part in order to determine which part it is Lot Code and Data Code Applications Lot Code and Data Code Reading can be accomplished with any one of the Reader Vision Tools The OCR Optical Character Recognition Vision Tool is used to read human readable characters The 2 D and 1 D Readers are used to read information symbols printed on the product OCR The OCR Vision Tool can be trained to read any character not just letters or numbers Usually this type of application requires positioning That is the label is not located always in the same location This problem requires more Vision Tools to provide a position reference As mentioned before the OCR Vision Tool itself can be used for position reference The user simply needs to create an
84. cked Omnidirectional RSS Limited RSS Expanded RSS Expanded Stacked and UCC EAN 128 When reading a composite code place the Vision Tool over the 1D part of the code The Vision Tool will automatically search for the 2D component Since this type of Vision Tool consists of a line it is susceptible to noise To overcome situations where the noise causes codes to be misread the Vision Tool contains an option to increase the scan lines By increasing the scan lines the user can rely on the output from most of the lines instead of all of them This will allow some lines to misread the code with the Vision Tool still getting the desired result This option basically creates a number of copies of the Vision Tool parallel to the original one at a user defined distance and groups all those Vision Tools into one When the position of the code is not consistent from image to image the area based version of the 1D Reader Vision Tool can be used This Vision Tool will generate parallel scanning lines starting from the origin line progressively toward the opposite side until it can read the code If the opposite side of the parallelogram is reached and the code was not read the Vision Tool will fail This Vision Tool will handle translation of the code and some rotation but it will not try to determine the orientation of the code 77 An option is available to perform grading on USS 128 UPC EAN Interleaved 2 of 5 USS 39 Codabar and Code 93 barcodes This
85. command is useful in determining if an IP address belongs to a Vision Sensor system or another node on the network TCP IP Subnetting Please note that the creation of custom subnets is beyond the scope of this appendix and so will not be discussed This section will only discuss default subnets i e 255 0 0 0 255 255 0 0 and 255 255 255 0 some key terms relating to subnetting and some basic rules on setting up IP addresses with the default subnet masks Subnetting is a common technique among network administrators to segregate a network so that network traffic remains in certain areas or subnets If a device in one subnet needs to communicate to another device in another subnet and both devices reside on the same physical network a router will be required see the definition of a Default Gateway to provide that link between the two areas However if the two devices reside in the same subnet then no router is required and the two devices can communicate with each other As a rule of thumb if the subnet mask is 255 255 255 0 on all devices then the first three numbers of an IP address which is the Network ID e g 192 168 203 1 will need to be the same and the last number which is the Host ID e g 192 168 203 1 192 168 203 2 192 168 203 3 etc will need to be unique in order for those devices to communicate with each other Similarly if the subnet mask is 255 255 0 0 on all devices then the first two numbers of an IP address wil
86. ction Vision Tool The Defect Detection is a Flaw Detection Vision Tool that can be used to easily identify detects in a part or object that is consistently placed part or a position referenced from another Vision Tool This Vision Tool learns the pixel pattern contained in the rectangle polygon or ellipse and compares the subsequent images to the learned one Figure 42 shows an image sequence where the part that is present in the first image is being inspected for errors Figure 42 Sample images of defect detection vision tool with extra material and missing material In the example the Defect Detection Vision Tool learns the first image and detects defects characterized by either extra information in the background or missing portions of the part As the Vision Tool inspects 75 the second image it finds the extra feature in the lower left section of the part It also detects the missing portion on the right side of the part A powerful feature of this Vision Tool is its ability to ignore areas around the edges by using an image mask The image mask places a lower weight on areas around the edges since they are likely to change from image to image The mask can be created by multiple images and it can be expanded or shrunk manually Therefore the Vision Tool is less likely to report errors near the edges The Defect Detection Vision Tool can be set to pass or fail based on the total amount of errors detected inside the Vision Tool or
87. d connecting to the I O breakout board Unpacking and Powering the DVT Vision Sensor Connect the keyed RJ 45 Digital I O and power cable to the DVT Vision Sensor typical part number CBL5 D10 Note The cable used for The DVT Vision Sensor has a male 15 pin high density DB sub connector on one end and a keyed 10 pin RJ 45 connector on the other end Connect the RJ 45 Ethernet cable typical part number CBL C10E Note If you are connecting the other end of the Ethernet cable directly to a PC as opposed to a hub make sure to use either a crossover Ethernet cable CBL C10EX or a crossover connector CON RJ 45N 21 A Connect the opposite end of the digital I O amp power connector High Density 15 pin D connector CBL5 D10 to the DVT I O breakout board CON IBOB Or if you do not plan on using the breakout board cut the connector from the 15 pin cable and wire directly into power and I O destinations Connect a 24V DC power supply to the DVT I O breakout board using the last three screw down terminals Note For laboratory use a power supply is available from DVT The part number is ACC 24 NA for North America This power supply uses the power jack on the DVT I O breakout board The isolation breakout board contains two sets of terminals one that is directly connected to the Vision Sensor and one that allows for the use of opto isolation modules As we saw in the previous steps the port
88. d of the saved average color e Optical Density is the second option in this case the color difference will be computed on a base 10 logarithmic scale This color space is mostly used in the printing industry RGB shows the reflectance of the measured sample but Optical Density shows the absorption The average Cyan Magenta and Yellow density is displayed The reported color deviations represent the change in optical density of CMY components compared to the Closest Color Color Difference is the maximum of DC DM and DY e La b AE this is CIE LAB Please note that La b values are approximate Standard formulas are used to compute these values e LC h AEcmc L is the Luminance or Intensity component of the sample C is the Croma or Saturation component and h is the Hue angle Color difference is AEcme During Inspection the average color of pixels under the Tool shape is found and displayed in the result panel Depending on the color space used the distance between this point and every color in the list is computed The Closest Color is the one with the smallest distance This distance is displayed in the results panel as Color Difference Figure 52 illustrates how the distance is reported in the RGB space The Vision Tool computes the Euclidian distance from the color found in the image to all the learned colors to determine the closest color Once this color is found the Vision Tool reports the color difference in each channel R
89. e DVT Vision Sensor IP 192 168 0 242 amp PC IP 192 168 0 240 Please refer to the section on subnetting later in this appendix To find the DVT Vision Sensor s current IP Address note the Vision Sensor s serial number on the back of the sensor s case and find the appropriate DVT Vision Sensor serial number in the serial number column of the Network Explorer Note the corresponding IP address in the IP address column Type ping replacing with numbers to check if an IP address is connected to the network This command can be useful in determining if a node is powered up operational and physically connected to the network COGNEX 114 Type arp a from a DOS prompt to view the ARP Address Resolution Protocol table The response should look something like this CAWINDOWS gt arp a Interface 192 0 0 111 Internet Address Physical Address Type 192 0 0 211 00 90 68 00 00 42 dynamic 192 0 0 212 00 90 68 00 00 42 dynamic 192 0 0 253 00 60 97 4f c0 45 dynamic The Internet Address column refers to the IP addresses you ve recently communicated with The Physical Address column contains the corresponding MAC Addresses for the IP s in column 1 DVT Vision Sensors will have Physical Addresses starting with 00 90 68 In the case above 192 0 0 253 is not a Vision Sensor but another PC on the same network as the named Interface The ARP table is cleared approximately every two minutes The arp
90. e when the threshold type is intensity based The output of the Vision Tool is the distance in pixels between the edges of the part Figure 39 shows the use of both line and area based Vision Tools Line Vision Tools called Measure Across Line can only measure the distance along the line 72 Result Table Product5 3 Show Graph Name Output Result n Inspection Trigger i Image Acquisition Vv vertLine Distance 124 617 pixels Contrast Vv a skewLine Distance 128 863 pixels Contrast Vv SlareaToo Width 123 909 pixels Angle 0 1 Vv Ei Inspection Res E Communications Figure 39 Caliper type Vision Tools measuring the height of a part As the figure illustrates more precision can be achieved using the area Vision Tool called Measure in Area Line Vision Tools require that the Vision Tool be drawn at a perfect 90 degree angle with respect to the edge of the part None of the line Vision Tools in the image is drawn in such way so the reported distance is greater than the actual distance Area Vision Tools on the other hand use many scanning lines and each scanning line provides a data point The algorithm then fits a line along each set of points and reports the distance between those lines as well as the angle between them If the angle is other than zero degrees the algorithm averages the maximum and minimum distances that it calculates from the data points in the Vision Tool The are
91. e 1 Member of The DVT Product Family the DVT 535 Vision Sensor The other two devices available in the DVT Vision Sensor Product Family are DVT LineScan LS Sensor The LS or LineScan sensor uses a grayscale imager with resolution of 2048 by 1 As a part moves through its field of view it can quickly acquire a single row at a time without suffering from motion blur due to long exposure times These rows can then be combined into a single high resolution image or processed one at a time indefinitely This allows acquisition of very high resolution images and inspection of high speed continuous materials Unwrapping of curved surfaces high speed continuous material inspection and high resolution image acquisition of moving parts are the main advantages of using a LineScan sensor 11 Inspection of those images is no different than with any of DVT s other Legend series cameras It has the same form factor as the other DV vision sensors It should be used with an external light that offers a very high intensity minimizing the exposure time Additional information can be found later in this manual The Extreme Scanner XS Vision Sensor uses the precision of a CCD to read 1D and 2D codes and characters It is the only industrial barcode reader to include OCR OCV capabilities Reading up to 200 codes per second the Intelligent Scanner is the leader in speed It can read the following codes BC412 PDF417 Codabar Code 39 Code 128 Interleaved 2 of
92. e Color Vision Tools the color space should be explained As was mentioned before color systems report four different values from each pixel Those values refer to the color content and the intensity level The color content is broken into three different coefficients to indicate the content of each basic color Red Green and Blue Any color can be created using the correct amount of Red Green and Blue so by having the system report the contents of all three basic colors any color can be represented in the system memory The fourth parameter that is reported is the intensity level This parameter would be the equivalent to the intensity as discussed for grayscale systems and is computed from the values obtained for the basic colors according to certain weight associated to each one based on the wavelength of the color All four parameters R for Red G for Green B for Blue and I for Intensity range from 0 to 100 so color identification occurs in a three dimensional space of R G and B coordinates whereas the intensity is an independent value Figure 49 shows this color space The X Y and Z axis are the R G and B components A certain color could be defined by three coordinates however that will give a very specific color In practice colors are defined by ranges of R G and B This defines a volume instead of a point as shown in the figure Points inside that volume are of that color points outside that volume are not of that color
93. e Vision Tool is drawn The different shapes are applicable to different cases thus the user should be familiar with the application and the part to be inspected and then select a shape accordingly An important difference between line and area Vision Tools is the processing time While area Vision Tools might be the best choice to make the inspection reliable they take more processing time than line Vision Tools Besides the basic line and area Vision Tools Intellect has other specific shapes available for certain applications Those shapes will be covered as the specific Vision Tools that use them are explained in the next chapter PreProcessing Operations In Intellect Preprocessing is available in the Preprocessing Vision Tool group as well as in individual Vision Tools Image quality is always the most important factor for setting up an inspection Sometimes a minor change in the lighting technique makes a big difference for the image However in many cases users have limited control over the physical setup of the system so another way to deal with noisy images must be used For those cases some Vision Tools have a built in number of operations that process the image before a threshold is applied These operations do not actually alter the image they alter the perception of the image for the selected Vision Tool Since Vision Tools can overlap altering the actual image would affect the result of every Vision Tool analyzing it The availa
94. e center of the blob to e the point that is farthest away from it R lt R gt e Radius Object Counting Count in Area Vision Tools The Count in Area Vision Tool in Object Locate mode use advanced algorithms to learn the edge characteristics of an object and find occurrences of that object in subsequent images The Object Locating mode can be applied in a variety of Vision Sensor applications including Flexible feeding motion control robotics Parts could be presented in any orientation and may overlap e Short product runs The key to these applications is quick setup because of the variety of parts manufactured e Position finding referencing The Object Locating modes learning ability means quicker When the Object Locate mode is selected the Vision Tool extracts edge segments of the part that are contained in the learn region of the Vision Tool The edge segments describe the geometry of the object Since the Tool uses edges it is less sensitive to lighting and intensity changes in the image making it very robust However the increased robustness of the Vision Tool comes at the expense of inspection time The list of features is kept in memory and the Vision Tool uses that list as the learned model In subsequent images the algorithm searches for the features contained in the model to determine the presence of the learned object The double area Vision Tool uses two areas The inner area is for learning the o
95. e found in the image The user can select the acceptance level to discard parts that are barely visible or severely damaged Measurement nspections Measurement applications involve measuring diameters widths height and other key measurements of an object Usually a combination of Measurement Vision Tools solves the problems When more operations are needed scripts can be used For instance scripts or the Statistic Vision Tool offer the flexibility needed to maintain running averages between inspections 96 Techniques for Better SubPixel Measurements Lighting Backlighting should be used for measurement applications whenever possible This technique consists of placing the part over a plane of light to highlight its contour The image produced by such arrangement simplifies the job for measurement tools and makes them more precise too When backlight is used on objects with curved surfaces the light should be masked or collimated to obtain better results Figure 62 shows examples of the use of masks and collimators The image on the left uses standard backlight Since the object being inspected has curved sides the light produced at the far ends of the light source bounces on the upper regions of the part and is directed towards the Vision Sensor This causes the Vision Sensor to see fuzzy edges making the measurements less reliable When this happens edges tend to be defined by transitions of as many as 10 20 pixels The second examp
96. e more flexible the Vision Tool is the more susceptible to noise it becomes That is if background noise or even other parts in the image present some of the features that the learned model contains those regions will be identified as a new object The parameters that allow the Vision Tool to be more or less flexible are e Scale Tolerance Allows the Vision Tool to find bigger and smaller objects e Minimum Match Score These indicate a minimum percent of features and perimeter that must match the learned model for the object to be indicated as a match e Locate Pixel Distance The pixel distance refers to the acceptable distance of the found edge from the model edge Increasing this distance will make the Vision Tool less sensitive and increase the match score 63 e Fine Coarse Slider You can select the resolution at which Object Locate finds the part at The default setting is Fine Medium resolution is 1 4 of the original area and Coarse is 1 8 As you go lower in resolution the effect of noise becomes smaller but the accuracy in the found location becomes lower With Auto checked it starts at the coarse resolution and then fine tunes the position of the found object all the way up to the fine resolution If you have the slider at Medium resolution with Auto checked it stops at medium resolution With Auto resolution in 1 3 OL becomes more reliable and faster at the same time All these categories cons
97. e set to maximize security The access control is independent of the PC being used the access control information is stored in the internal flash memory of the Vision Sensor Please be sure to write down your administrator username and password There is no means of recovering from a secured system without a valid username and password 29 Digital O Configuration Vision Sensors have a number of configurable I O lines The DVT Vision Sensor contains eight I O lines The I O lines can be configured to better suit the user s needs Vision Sensors do not have fixed input or output lines Every I O line can be configured as an input or as an output depending on the user s needs This assignment is a system parameter because another device will be connected to the I O lines and this cannot change between inspections It should be mentioned that the number of I O lines in the DVT Vision Sensor can be increased to 24 I O points by the DVT remote Ethernet I O device CON IOE Input Functions Inputs on the Vision Sensor can serve one of many functions The following table summarizes these functions Input Function Product ID Bits Table 3 Input Functions Purpose Each line will represent a digit to make up the binary code that identifies a product based on the assigned Product ID Product Select Toggled when Product ID bits are active to select a Product This signal tells the Vision Sensor that the Product ID in bina
98. e the processing time Figure 48 shows an image containing non conventional characters This type of character is very difficult to read because of the deformation that it contains The first image shows the text itself and the second one the first attempt to isolate the characters Figure 48 Use of the extraction tools to separate individual characters As the image shows the last two letters share the same red bounding box That means that the algorithm failed to correctly isolate every character When the extraction parameters are being used in this case maximum character width and advanced maximum character width the Vision Tool makes a better decision as to where the characters end and they are correctly isolated The next step in the use is the training phase The Vision Tool needs to be told what the extracted characters represent This option is very powerful because anything can be trained from user s handwriting to stroke characters The only characters that are not trained are the spaces because the Vision Tool ignores them Also for applications where the speed of the process causes the characters to vary several instances of each character could be trained to maximize reliability As characters are trained a font list is created and kept in the Vision Tool This font list can be backed up to a PC for security purposes If another system is to be reading the same labels the font list could be loaded into the new system without the
99. earn Correct Error wes Other Colors No Compare Colors to Colors in Merge Learned successive images Colors into One or Export Color Figure 56 Process for single color learning As the process in the figure illustrates single color learning does not mean the use of a single color but the learning of one color at a time By following this process the user will end up with a list of colors or 92 a single color representing the list that describe a part or a set of parts and can be used for future inspections For this process only one color can be seen by the Vision Tool when the colors are being learned Any attempt to learn a color when two or more colors are seen by are inside of the Vision Tool will result in incorrect colors being learned The second use of the Vision Tool is the multi color learning This process involves learning multiple colors at the same time The process is illustrated in Figure 57 SET PARAMETERS FOR LEARNING COLORS TEST SET OF COLORS EED ON COLOR THAT REPRESENTS ALL LEARNED COLORS COMPARE LEARNED COLORS TO MERGE LEARNED COLORS IN COLORS INTO ONE SUCCESSIVE IMAGES OR EXPORT COLOR Figure 57 Process for multi color learning This process is used to learn the colors of a complex part one that is not of a well defined color The Vision Tool is drawn over the entire area so all the colors are inside the Vision Tool and the process begins by
100. ed If the images are not well focused the edges will not appear as sharp In those cases the user needs to give the Vision Tool an idea of the transition width to better calculate edge positions Figure 36 illustrates the use of this option The Vision Tool on the top edge does not find the fuzzy edge with the default edge width setting The bottom vision tool s edge width setting is set much higher E Static gt Result Table Eq Figure 36 Area Measurement Vision Tools in presence of fuzzy edges The gradient graphs indicate the width of the transition e Use Best Edge This option is for noisy images Sometimes background noise produces minor peaks in the gradient graph In cases where those peaks happen to reach levels above threshold this option will discard them and keep only the highest peak The use of the Best Edge option is illustrated in Figure 37 In this example if the option was not selected the Vision Tool would report the edge close to pixel number 20 which is where the first peak above threshold is located The use of this option makes it report the true edge instead because it is a better defined edge The Vision Tool on the left is not using this advanced option and the data points 70 generated by the presence of noise cause the output line to be calculated at an incorrect location The second Vision Tool uses this option and the output line is correctly drawn over the edge of the part MM Static
101. ed of the Vision Tool The density format and type of error correction can be auto detected However if these parameters are known they should be manually specified to obtain faster reads Other parameters that can be set include code symmetry dot size and color dark code on light background and vice versa The SnowFlake Reader Vision Tool can be set to pass based on a match string Optical Character Recognition OCR The DVT OCR Optical Character Recognition is a powerful industrial reading tool that provides robust character reading and verification capabilities Itis designed for reading lot or batch codes serial numbers labels product IDs and symbols in the industrial environment It is not designed to be a page reader that reads scanned in documents Intellect s OCR Reader Vision Tool can read alpha numeric characters using either a user trainable font set or a fixed font set The trainable DVT OCR Vision Tool is based on feature extraction to learn characteristics about a character and then finds the closest matching character on subsequent inspections Feature extraction computes the features of a graphical object and compares them to features of the trained or learned character set The fixed font OCR Reader uses a non editable fixed font library that defines the character set The fixed font reader is best used when the background is noisy but the characters are consistently printed The feature extraction process of the traina
102. ed program In this case you will see a DOS console appear At the prompt type open followed by a space and then the Vision Sensor s IP address e After you are connected you will see some information about the system displayed At the question mark prompt type the following command without the quotes Fibdc You might not see what you are typing if you do not have local echo enabled in the telnet program e You should see the message Erasing Flash After the process is completed you will receive the question mark prompt At this time permanent memory has been erased and you should close the telnet program Appendix E Breakout Boards Isolation Breakout Board The isolated breakout board for the DVT Vision Sensors not only provides a convenient method to connect digital I O power and strobe illumination lines but it also enables the use of isolation modules The board is housed in a metal plastic DIN Rail mountable case with powder coating on top The breakout board is 126mm wide by 149mm high by 45mm deep including all necessary cable clearances The board has two main ports The port on the right includes I O strobe and power screw down terminals The I O lines on this port are to be used when no isolation is necessary The second port on the left side has the I O connections to be used in conjunction with isolation modules The optional isolation modules can be acquired from third party companies to p
103. efer to Figure 12 for a diagram illustrating the following procedure First set the binary bit pattern of a Product s ID number on the Product ID Input lines When the Product ID bits are loaded in this case Product ID 1 which is 01 in 2 digit binary code the Product Select line should become active This tells the Vision Sensor to read the data bits from the Product ID bit lines When this signal is sent to the system a response can be read indicating a successful unsuccessful operation Two outputs are dedicated to alerting the user of the success or failure of the digital selection process Product Select Pass and Product Select Fail Reading one of these should be enough to determine the success of the product selection 37 Prodi Bit of binary product ID pies D Bit 1 of binary product ID Product Signals the sensor to read Select the product ID bits Typically a photoeye or Active while acquiring or Output inspecting an image neparni Indicates inspection result Pass Definable User definable output Select Indicates that the product Pass selection was successful o z c o cu 5 o Figure 12 Select a Product using the digital inputs The above diagram shows the I O timing of the Product Selection process For example if a Product ID of 3 is selected but the sensor has only products with ID s 0 1 and 2 Product Select Fail should be high and Product Select Pass should be low When the product selecti
104. emove process will delete from the aforementioned group of colors that are in the region of interest of the Vision Tool at the time this action is executed The add operation will do the opposite it will add colors that were not present in the previously learned and merged group of colors After executing any of these options the user will end up with multiple colors grouped together under a single entry on the Manager tab Another feature that these Vision Tools present is the digital relearn They can be programmed to expect an external signal digital relearn and when the signal is received the Vision Tool executes one of several operations These options go from a single color learning operation to automatic multi color learn and merge processes The digital relearn signal can be used to change the match color as well The match color is the color against which every image is being compared to determine a PASS FAIL result The uses for this Vision Tool are e To detect the correct color The Vision Tool can be set to pass or fail based on color variation e To detect the right amount of color The Vision Tool can be set to pass or fail based on changes in the amount of a certain color 85 e Toidentify parts The Vision Tool can be used to determine which part is in front of the Vision Sensor based on the best match feature which tells the user which color from the list best matches its original size in pixels e To export colo
105. en a specific color is desired and the flaw occurs when the color does not match When the flaw can be isolated using a threshold level the other tools can be used to find it Pixel Counting and Feature Counting Vision Tools are the Vision Tool that take the least processing time Counting I nspections Counting applications require parts or features of a part to be counted The Vision Tools in the Counting Vision Tool group are typically used for counting applications The Edge Feature and Pattern Counting algorithms in the Count along a Line Vision Tool should be used to identify features along a line arc or another predefined shape These Vision Tools scan along that line counting the edges or features found They take little processing time but they require that the pattern in which the features are arranged be known Blob Counting should be used when counting parts that change the position and that do not touch each other The Blob Vision Tools will count two parts as one if the blobs touch one another If the parts are separated this type of Vision Tool offers a very reliable solution at a relatively high speed When parts can be touching or even overlapping the ObjectLocate algorithm in the Count in Area Vision Tool should be used since it learns the shape of the part and will find it even if the entire shape is not visible In this case the Vision Tool will report that there is a part when a certain number of features learned from the part ar
106. er s IP address except for the last number For instance Computer 192 168 1 113 DVT Vision Sensor 192 168 1 32 If you are not sure about which IP address to use you should ask your network administrator See Figure 7 a G Actionsy Camera ALEX_515TEST Properties B E General Properties TN comers Name ALEX_515TEST Group Network Settings IP Address Selection Static IP Address 10 22 50 239 IP Mask 2525 Default Gateway 0 0 0 0 Eth Link Speed Duplex Auto E Features MAC Address 00 90 68 01 29 46 Serial Number 515100003 Camera Type Vision Sensor Model DVT 515 Application Intellect version 1 3 0 DEBUG Detected on Broadcom 440x 10 100 Integrat Feedback Status Unknown Figure 7 Properties Window e If the IP address is already being used by another device The software will return to the original address Simply go back and edit the systems IP address once more to a number that is not currently being used An icon will appear next to the name of the camera if it is unreachable or in Diagnostics Hint After configuring your DVT Vision Sensor with its new IP address you should affix a label to the Vision Sensor with the Ethernet properties so that you do not forget this important information Repeat these steps for each DVT Vision Sensor you have When complete the PC and all sensors will have unique IP addresses Connect all of the systems to a hub or multiple hubs and the hub to you
107. er can execute these functions on the Vision Sensor without exiting Intellect Refer to the Intellect help files for a complete list of commands Vision Sensors can receive on the system terminal o Script Debug Window Special window dedicated to receiving Debug statements from scripts that help in troubleshooting the code Please refer to the script documentation for more information about it o Datalink Output Window The DataLink View window shows the information that is sent out the data after each inspection The information that is sent out the datalink port is configured for each product in the Communications Manager o Options Gives access to advanced features From this menu the user can enable advanced features for many Vision Tools set parameters for the Vision Sensor itself and activate deactivate buttons from the Vision Tool toolbar The Image menu gives the user control over many imaging parameters Most options in this menu are very general such as play stop record create static image zoom in zoom out etc The image menu also allows you to configure the image sequence when connected to an emulator The System menu contains managers and settings that are at the system level including background scripts communications network connections calibration coordinate transformations and system administrations o Network Explorer This options opens the network communications managers which allows you to connect u
108. es 73 Ethernet Adapters Highlighting the appropriate DVT Smart Sensor in the right pane causes the Vision Sensor s Property window to appear The Vision Sensor s Property window allows the Vision Sensor s IP Address and subnet mask to be changed COGNEX 113 amp Properties E F actions 2 Camera DYT Smart Camera Properties 3 General Properties Name DVT Smart Camera Group MAC Address 00 90 68 01 01 cF Serial Number 53025133 Network Settings IP Address 192 168 2 107 IP Mask 255 255 0 0 Default Gateway 0 0 0 0 Eth Link Speed Duplex Auto Settings Camera Type Smart Camera Model Legend 530 Application Intellect Version 1 1 1 Build Feedback Status Up TCP IP Troubleshooting Tips IP addresses for each PC and for each network card installed on the PC and each device that uses the TCP IP protocol such as the Vision Sensor is required to have a unique IP address IP addresses should not use 0 or 255 as the last value e g 192 168 1 0 and 192 168 1 255 respectively These are reserved and have special meaning Addresses that end in 0 specify all addresses for a particular subnet Addresses that end in 255 specify a broadcast packet that is sent to all hosts on the network With both PC and Vision Sensor using the Subnet or Address mask of 255 255 255 0 the IP addresses of the PC and the DVT Vision Sensor must be identical for the first three values and unique in the fourth value Exampl
109. es to speed up the process or to get the best possible image A parameter directly related to the digitizing time is the partial window acquisition explained below When partial image acquisition is being used the acquisition time decreases to a fraction of the selected digitizing time This fraction is proportional to the size of the image being acquired Partial Image Window Some applications may not need to process the entire image but just a portion of it if the part to inspect is consistently located Vision Sensors allow the user to select a specific window within the image so only that window is acquired One portion of the total inspection time is the image acquisition The Vision Sensor CCD with a resolution of 640x480 pixels takes approximately 13ms to transfer the image from the CCD into memory This time is proportional to the number of rows being acquired Reducing the acquisition window to 320x240 for example would cut the acquisition time to approximately 1 2 the original value Note For some imaging sensors the area to the left of the desired partial image must also be transferred as seen in the figure below Therefore to achieve the fastest image transfer choose a partial image region that has the least amount of rows and is as far left as possible 35 Figure 10 Partial acquisition window for 535 and 545 systems Antiblooming Blooming effect occurs when pixels absorb so much light that they saturate and c
110. eshold being calculated The pixel graph on the left shows the presence of the light part The threshold is correctly calculated at 50 of the difference between the lightest and the darkest pixel The pixel graph on the right shows the pixel graph for the same Vision Tool for the case where only background is present in the image with intensity levels between 5 and 12 In this case there is no part but the Vision Tool still computes a threshold because it can still find a lightest and a darkest pixel In order to avoid this case the user can select the Minimum Contrast option and set a minimum contrast that must be matched to even compute a threshold For the second case explained above a minimum contrast of about 10 would prevent this Vision Tool from computing a threshold and thus will cause it to fail Vision Tool Graphs Just like at the Product level Intellect offers graphs to display Vision Tool level information This information is tool specific it could be generic information Pass Fail etc or very specific Vision Tool information The latter depends on the Vision Tool being used The first and most common Tool graph is the Pass Fail graph It serves the same purpose as its product level counterpart but the data refers to a specific Vision Tool see Product Graphs for more information The rest of the Vision Tool graphs could be classified as Image Graphs Image graphs are graphical interpretation of the areas analyzed by
111. for Images Directory C AEVersionControl DVT Training DVTOnLineTr File Type BMP Numbered Image Sequence Filename Prefix First Image Number Current Image Last Image Number ok Cancel Help Here the user has two options type everything manually or click on the Browse for Images button to find the desired images In order to load the Product or System file the Open action from the File menu should be selected Look in DVTTraining C3 DvTAdvTraining CDV TBasicTraining 5 DYTOnLineTraining CDvTwebTraining E VirtualTour File name Kas y m m Files of type DVT Files dvtiprod dvtisys2 dv iscr bmp Y C Open as read only With the images loaded the user can make any change that does not depend on physical setup to the system just like if Intellect was connected to a Vision Sensor When the user is done step 1 should be repeated but in this case for the Emulator A system or product file can be saved from the Emulator in the same way that it can be saved from the sensor This procedure allows the user to set up the inspection parameters in the Emulator and then load those as a System or Product file into the Vision Sensor Note If users want to run the Emulator but they have no images a standard graphics program could be used to create some images The images need to be 256 color bitmaps of the same resolution as the Vision Sensor to be used 640 by 480 o
112. for a product It lists all the Vision Tools in it as well as their outputs The Inspection Statistics table accessed by double clicking on Inspection Results in the Result Table is particularly useful for troubleshooting This table keeps count of passed inspections failed inspections pass and fail percentages image acquisition timing inspection timing inspection overhead and total time for inspections These parameters help users determine when there might be a timing issue with the inspections Figure 18 shows an Inspection Statistics Table a a 9 DJ Inspection Results Properties v Result Type Maintain A l4 Feedback E Basic Feedback Result PASS Pass o 100 0 Fail 0 0 Pass Count 698801 Fail Count 235 Timing ms 44 1 amp Original Inspection Timing ms Image Acquisition 15 2 Inspection 31 8 10 5 Inspection Overhead 21 9 Total Time 47 7 Current Inspection Timing ms Image Acquisition 15 2 Inspection 28 9 Total Time 44 1 X Figure 18 I nspection Statistics graph Vision Tool Parameters Vision Tools are the workers inside Vision Sensors Each one is assigned a specific task to extract information from the image The combination of all the tasks performed by the Vision Tools makes up the entire inspection The main Vision Tool parameters are the Vision Tools shape processing options threshold and PASS FAIL conditions Vision Tool Shape Vision Tool creation is a very simple point and click proce
113. ften changed when using Line Scan systems e The Products menu contains product level information and settings This includes product level communications settings like datalink strings SmartLink data transmissions image acquisition properties and product management functions e The Tool submenu offers access to Vision Tool parameters From here the user can edit Vision Tool settings and create Vision Tools e The last two options Window and Help have standard Windows functionality The Window option is used to customize the user interface The Help menu brings up the Intellect help files which are rich in content and examples The Toolbars contains buttons that offer shortcuts to the most frequently used functions of the software Every button offers a tool tip that is when the cursor is placed over a button a message is displayed on the screen indicating the functionality of the button The toolbar area contains four toolbars System Image Product and Tool toolbars The System toolbar contains buttons to connect disconnect from the system open a file undo an operation white balance save system to flash and settings for inspection triggering The Image toolbar contains buttons to change the exposure time which is displayed in milliseconds a button to control the strobe lights antiblooming control and controls for both the Vision Sensor and the user interface The controls for the user interface contain a Play butto
114. g a Standard DVT Grid allows for a quick and easy coordinate transformation by placing a special calibration grid in the field of view and performing a calibration A custom grid allows the user to use a grid pattern with a set dot pitch A script calibration allows the user to define pixel point to real world point pairs in script Itis recommended to use the standard grids when possible These grids are available on the DVT website in the download section The steps to create and calibrate a Coordinate Transformation are explained below e Add a new Coordinate System in the System Menu section e Select the Grid Type e Place the appropriate grid in the Field of View e Click right Mouse button on the Transformation in the System Explorer and select Calibrate Coordinate System e Open the Product Manager in the Product menu and Select the desired product to use the Coordinate system In the properties window of the product set the Coordinate Transformation for the product All the measurements and positions will now be displayed in the appropriate real world system You can apply a Coordinate Offset and scaling factor to the Coordinate system to alter the reported position and measurement values Color Sorting I dentification Applications Color Sorting applications generally involve monitoring the color s of an object to determine which object it is The Color Identification Vision Tool can be used to determine the part based on the distrib
115. g rate for the transfer Note by default the master will transfer 103 data both at the specified polling rate and at the end of each inspection In order to specify the block of registers to transfer the user must be aware of the difference register sizes for the different data types used by the Vision Sensor Modbus registers are 16 bit registers Therefore it is important to take into account is the size of the different DVT data types This becomes a very important issue when trying to transfer data Different data types occupy different numbers of registers in memory If a certain value is saved to memory using a script tool and that particular piece of data needs to be transferred to another system the user has to know the exact number of registers that the piece of data occupies in memory Table 4 shows the size that every different data type occupies in memory For example if a measurement tool outputs a float that number will occupy 32 bits So according to the size of the Modbus registers explained above this requires the transfer of 2 Modbus registers Table 9 Size of the different data types in bits and Modbus registers Size bits Size Modbus Registers 1 2 4 2 4 8 per char 1 1 per 2 char 1 For more information about Modbus protocol and Modbus transfers see the DVT Integration Notes section of the DVT website If the transfer of data needs a more explicit process Modbus transfers might not be the best app
116. gering the system the user can define a fixed delay after trigger if the detection of the part to be inspected cannot be made at the precise moment that the part is in front of the Vision Sensor This way the user can have a Tool detecting the position of the part and triggering the system but the Vision Sensor will not acquire an image until the part is precisely in the correct position FOV Balance FOV balance includes two different operations White Image Normalization and Dark Image Subtraction White Image Normalization is the process that was known as FOV balance in previous releases When the illumination is not uniform and the physical setup cannot be improved doing a White Image Normalization may be helpful The user can select to calibrate automatic process and activate a white normalization of the field of view in a certain region of the image or over the entire image This will correct the pixel intensities to make the illumination seem even and well distributed across the image or the selected region In general uneven light should be made even by changing the physical setup position source etc instead of using this option This procedure is not recommended for precision measurement applications in which the information contained in every pixel may be vital for the success of the inspection The Dark Image Subtraction available on all cameras is generally used in applications where the exposure time is high When this
117. he edge pattern that the user indicated it reports the distance from the origin of the Vision Tool to the location of the edge feature in pixels Figure 32 shows a line Vision Tool and its pixel graph C Pixel Graph posX BEAR z a Position Along Graph contras MEA Offset 62 38 PASS Figure 32 Position along a line Vision Tool and its pixel graph This Vision Tool can only corrects for movement in one direction However in most cases the part needs to be tracked in two directions of translation When that is the case another Vision Tool of this type needs to be created and a reference between them needs to be assigned That is the user needs to create two Translation Vision Tools one to determine the translation in one direction and a second one to determine the translation in another direction The second postion tool should reference the first position tool and all other inspection Vision Tools should reference the second position tool The creates the necessary position reference chain mentions earlier When looking for an outer most point of a curved edge increase the Scan Line Width in the Shape tab to get the effect shown in Figure 32 Besides providing a position reference for other Vision Tools to perform the inspection Translation Vision Tools can be used to inspect a part In applications where the position of a certain feature decides whether the part passes or fails translation Vision Tools
118. here are two different methods of configuring an Ethernet Terminal Controller The first one makes the Vision Sensor a TCP server expecting a connection on port 5003 In this port it exposes the System Driver which is the driver that receives most Ethernet commands to control the system The second configuration is as a TCP client In this case the system connects to a server with IP address 192 168 0 242 on port 5004 and sends DataLink strings to that 104 server This is indicated by the selection of the DataLink Driver This example demonstrates the two main types of configuration server and client After this is properly setup the communications should be established when the Ethernet Terminal Controller is started or on power up Industrial Protocols DVT systems support other methods for communications such as standard protocols EtherNet IP ProfiBus and DeviceNet EtherNet IP support must be enabled from the I O menu in Intellect and the power must be cycled for the changes to take effect It is disabled by default to avoid loading the processor with operations not used Using scripts the user can interchange data with other devices that support the protocol For more information about this type of connectivity please refer to the Script documentation and DVT integration notes SmartLink a different DVT product that can be connected to a DVT Vision Sensor can communicate via DeviceNet or PROFIBUS using expansion cards designed for that
119. high to active low Debounce times are used when the signal received by the Vision Sensor may not be stable such as when a physical switch is used If this is the case the user can select a period of time during which the Vision Sensor does not look at the line after registering a transition in the state of that line Filtering is used to filter noise spikes that may occur Output Functions There are several output functions that can be assigned to the I O lines The following table summarizes the available output functions and their meaning Any function may be assigned to any I O line Output Table 4 Output Functions Function Purpose After inspection is completed Pass is set to show that all Vision Tools within the Pass Inspected Product passed inspection After inspection is completed Fail is set to show that any Vision Tool within the Fail k Inspected Product failed inspection Busy is set after Inspection Trigger is read until the inspection result Pass or Fail Busy aiu is signaled Strobe 1 When active the corresponding strobe light source will be on during image exposure Strobe 2 When active the corresponding strobe light source will be on during image exposure Strobe 3 When active the corresponding strobe light source will be on during image exposure Re o rc Signals a conflict between inspections trying to use the same system resources Conflict Typically signals that an Inspection
120. ialty positioning Vision Tool used to find the location of a straight edge by finding edges and fitting a line to the found edges This Vision Tool reports a rotation angle e Circle Fit Specialty positioning Vision Tool used to find the location of the center of a circle It is important to note that these are not the only Vision Tools that could be used for providing a position reference for other tools They are just the simplest and easiest positioning tools available For more information on which Vision Tool to choose or how to approach applications where part tracking is needed consult the section Dealing with Part Movement in Chapter 4 Position along a line arc Position along a line or arc Vision Tools locate the absolute position of an element in an image in cases where that element s position changes between inspections There are two types of shapes Lines and Arc Lines find detect translational movement and arcs detect rotational movements Translational lines determine the position of an edge or a pattern edges and patterns were explained under Count along a Line Vision Tools The option to locate patterns should be used when the application allows for it because it makes the Vision Tool less sensitive to noise This type of Vision Tool reports the distance from the origin of the Vision Tool It searches the pixels from the origin in the direction of scanning set by the direction in which the Vision Tool was drawn When it finds t
121. if you are erasing flash from Intellect you should select Yes when the corresponding message appears 12 Wait for approximately 30 seconds If the progress bar closes before that make sure the correct Vision Sensor is highlighted in the right hand pane and right mouse button click on the DVT Vision Sensor and select the Connect option 13 Before getting into Intellect the program will ask you if you would like to store the firmware to Flash Memory Choose Yes It will take a few seconds to store the file to flash memory Then the Sampled Image Display will appear in the User Interface of Intellect Erasing flash using Telnet This is a fail safe method to erase flash memory You should read this section and follow the instructions explained if the diagnostics version of the system you are trying to upgrade is older than version 0 28 or if the procedure covered in steps 10 11 above does not work After forcing the system into diagnostics mode and reassigning the appropriate IP address and net mask you can proceed to clear the contents of flash memory You should use telnet or any other terminal emulator to connect to the DVT Vision Sensor through Ethernet on port 23 which is the default port for telnet Telnet is included as an accessory in all versions of Windows e Click on Start then Run COGNEX 120 e Type telnet and press Enter e In Windows 2000 XP and NT telnet is included as a DOS bas
122. iginal size Figure 20 shows the inspection of a part with texture The texture causes some noise inside the part the first Vision Tool shown does not use any operation so it picks up all the noise Figure20 Example where the operations of Dilate and Close are used The second Vision Tool uses the operation Dilate which expands the part in all directions This helps with the noise but alters the area of the part The last Vision Tool uses the operation of Close and it successfully eliminates the noise and returns the part to its original size The user needs to remember that all these operations add some processing time The operations of Open and Close add twice as much processing time as the other two operations because they perform the basic operations twice Threshold Vision Tools use the information from every pixel to inspect images Every pixel contains a certain intensity level ranging from 0 to 100 Based on application specifications the user selects a threshold level to classify the pixels contained in the Tool as dark pixels below threshold or light pixels above threshold There are several ways to compute a threshold e Intensity Based Fixed Value This option lets the user manually select the threshold level This threshold has to be a number between 0 and 100 and it is considered a static threshold because it does not change from image to image e Intensity Based Percent of Path Contrast This is a dynamic thre
123. iles If the codes vary slightly in terms of size a Scale Variation can be set under the Advanced tab The enhancements to the algorithms include substantial improvement in processing time However for those time critical inspections some parameters can be adjusted to further improve processing time The 78 Minimum Gradient can be increased so that noise in the image is ignored during the searching process especially if there is good contrast between the code itself and the background Decreasing the region of interest may also improve the processing time This Vision Tool can be set up to simply read decode and output the data or to verify that a certain string is present in the code For the second case the Vision Tool will fail when the string is not matched It also includes a digital relearn option That is if the string to be decoded changes a signal could be sent to the Vision Sensor to relearn the matching string The DataMatrix code can also be graded The 2 D reader Vision Tool can be set to read SnowFlake codes Again the code does not have to be consistently located in the same place every time SnowFlake codes are designed for fast printing applications and dot matrix printers are generally used Figure 46 shows two examples of such codes D ee 9 s 58s mue eg 9 t mm o or e A b IN Figure 46 Examples of SnowFlake codes Several parameters can be set to improve the processing spe
124. ing Vision Tools The Preprocessing Vision Tool category contains Vision Tools that alter the image to help the other inspection Vision Tool accomplish their tasks more effectively In general the preprocessing Vision Tools reduce background noise increase edge or foreground contrast or move image pixels around Positioning Vision Tools The Positioning Vision Tools are a group of Vision Tools that are generally used to find the location of a part or a feature of a part The Vision Tools can then use the position information to either move other Vision Tools to the proper location for inspection or to guide an external robot or motion controller to the location Counting Vision Tools The Counting Vision Tools are a group of Vision Tools that are generally used to find a number of features of a part or the objects themselves in a region This information can be used to pass or fail an inspection for presence absence orientation or count Measurement Vision Tools The Measurement Vision Tools provide accurate measurements of objects and parts This group also contains Datum and Statistics tools Identification Vision Tools The Identification Vision Tools are used to recognize or identify a particular part or feature from a set of learned parts or features Reader Vision Tools The Reader Vision Tool Category is comprised of 1D Barcode readers 2D Barcode readers and OCR and OCV Vision Tools Flaw Detection Vision Tools The Fla
125. ing on the contrast found in those areas The user needs to specify a window size in pixels the software then calculates a threshold using the percent of path contrast method for individual windows making the overall threshold more robust when lighting and contrast are not uniform This method is the slowest of the thresholding methods e Gradient Based Fixed Value This method for calculation of a threshold uses the pixels intensity gradient That is it compares pixels with their neighbors in the image to determine local changes in intensity It then produces a gradient graph that has peaks where the highest changes are located The user needs to specify a threshold to separate the main edge s This method works in the same way as for Intensity based threshold as explained above NOTE This method uses pixel interpolation to calculate the best position for the edge providing sub pixel accuracy e OCR specific the OCR Vision Tool has three extra options for calculation of the threshold that will be discussed later on when the OCR Vision Tool is covered Vision Tool Result Vision Tools can be set to PASS or FAIL based on predefined criteria Usually the PASS condition is assigned when the parameter being checked is within the specifications The FAIL output is reserved for cases where the parameter being checked exceeds the specifications Every Vision Tool contains a custom set of rules for the user to set as the PASS FAIL criteria Th
126. inimize noise in your image background e Keep characters as similar to the learned characters as possible This type of Vision Tool has two different types of threshold intensity based and OCR Intensity based threshold methods include the previously discussed types static dynamic and color reference The OCR thresholds are unique to OCR Vision Tools This type of threshold is designed to maximize the extraction of the characters for more accurate readings There are three options for the use of the OCR threshold e OCR Computed Automatic intensity based threshold that makes an intelligent decision as to what is text and what is background and sets the threshold level to better separate those two It calculates a single threshold level for the entire area of the Vision Tool e OCRLinear Same as OCR Computed but designed for uniform variations in light It computes an individual threshold for the first and last characters and applies a linear variation of those values for the characters in between The user needs to specify how many characters blocks the Vision Tool is supposed to read e OCR Nonlinear Same as OCR Linear but for cases where the variation of the illumination is not uniform The Vision Tool in this case computes one individual threshold for each character This option requires more processing time than all others mentioned here This Vision Tool is very flexible the user can customize it to the application A great feature
127. ision Tools The pixel graph associated with this Vision Tool illustrates the pixels along the origin line left edge in this case The left line then becomes the origin line and works like a Translation Vision Tool The Vision Tool pixel graph corresponds to the origin line As it was discussed before pixel graphs are only compatible with line Vision Tool however in this case we have an area Vision Tool and a pixel graph associated with it Since the most valuable region of the Vision Tool is the origin line that is the line used for the pixel graph The pixel graph then shows a numerical value for both the angle of the part and the position of the edge or feature Area Positioning Vision Tools The Area Position Vision Tools search in an area for the location of a single object or feature that is trained This Vision Tool uses one of three different algorithms to accomplish the locating of an 67 object feature Object Locating Pattern Matching or Blob Analysis The position of the found object can be used for moving other Vision Tools when the inspected part moves in the field of view or it can be used in combination with a coordinate transformation to give the coordinates of a part to a robotic device When first drawn the Area Position Vision Tool will default to the Blob algorithm and the Vision Tool will automatically learn the object under the rectangle that is first drawn A larger search region rectangle will automatically be draw
128. ist of a number of different parameters for explanations about each one and how to change them please refer to the Intellect help files To understand how much to change the values please refer to the Vision Tool properties under Model Object a number of parameters are displayed corresponding to every object that is found in the image Image marking for this Vision Tool is similar from the others The user can customize it by choosing among two options Object Marking and Live Edge Image In Object Marking the found object is marked with edges that matched the learned model in green and missing edges of the learned object in red When displaying the Live Edge Image the relative strength of the extracted edges is show The brighter the intensity the stronger the edge This Vision Tool has many applications and uses including position feedback for another Vision Tool or to a robot or other external device However if the application consists of counting the parts the Vision Tool can be set to pass or fail based on the number of objects found Pattern Counting Count in Area Vision Tools The Count in Area Vision Tool in Pattern Match mode is used to check pixel patterns against a learned intensity template This mode uses a normalized grayscale correlation algorithm to find the best match of a learned pattern in the search region Therefore it is valuable when strong edges are not present when intensity changes occur and when large amo
129. istical Process Control SPC data This information might be as generalized as a PASS or FAIL signal or as specific as position feedback to a motion controller You can use the Intellect software to divide and conquer these tasks Intellect was designed to be easy to use for anyone DVT Vision Sensors Product Family The DVT Vision Sensor Product Family consists of the 500 family of products as well as the DVT Spectral Sensor The 500 family of products consists of the following Vision Sensors e DVT 515 Sensor 1X The DVT 515 uses a grayscale CMOS device with a resolution of 640 by 480 pixels It includes all Intellect tools except the Reader Vision Tools and the Spectrograph exclusive to the DVT Spectral Sensor e DVT 535 Sensor 2X The DVT 535 Vision Sensor is similar in functionality to the DVT 515 Vision Sensor but delivers more precision by replacing the image acquisition device with a CCD This camera is better than the DVT 515 system for precision measurement applications and analysis of parts that are rich in detail This camera has 2X the processing speed of the DVT 515 e DVT 545 Sensor 4X This vision sensor consists of a 640 by 480 pixel grayscale CCD and a high speed processor It combines the quality images provided by a CCD with the power of a fast processor to perform delicate inspections at a very high speed This vision sensor has 4X the processing speed of the DVT 515 10 DVT 542C Sensor 3X This is the basic c
130. istogram shows two well defined groups of pixels which may represent background darker pixels and the actual part lighter pixels Result Table Product2 Histogram 13 5 Show Graph Percent Piteli su tenut Level Figure 23 Screen capture of a histogram The third image graph is the gradient graph This type of graph plots changes in intensity values from pixel to pixel along the path of the Vision Tool It does not show the actual intensity value of the pixels 46 just the changes Sharp positive or negative peaks represent strong edges Figure 24 shows a pixel graph and a gradient graph for a certain Vision Tool amp Gradient Graph y 5 Show Graph Gradient value Fonton Wong Graph Pirels Figure 24 Gradient graph for a Vision Tool Notice how the gradient graph peaks where the pixel graph shows the biggest change in intensity levels Digital Relearn Digital relearn is an option that is present in many Vision Tools It refers to cases where the inspection consists of comparing something to a learned version of it Its use extends to the following Vision Tools Area Based Positioning Pixel Counting Area Based Counting OCR 1D and 2D Readers Label Inspection Bead Inspection Identification and Flaw Detection When these Vision Tools are created something is learned a shape a code a color etc When the Vision Tool performs inspections it uses the learned model If the applica
131. its region of interest That is the code does not have to be consistently located in the same place every time The Vision Tool offers robust draw and read performance The reader works through training on a certain code This training is performed automatically after the Vision Tool is drawn After the reader has been trained it collects information about the code and sets all trainable parameters Symbol Type e g ECC200 Symbol Size in terms of number of cells Module Type dark modules or light modules Mirror Image Threshold Type and Cell Sample Size For a detailed explanation on each of these parameters consult the Intellect Help Files The information learned about the code is then used in subsequent images to read each code If a code cannot be initially read during the training phase the user can manually set some of the known trainable parameters to help the Vision Tool find and read the code The Vision Tool searching process does not use an intensity based threshold The threshold indicated under the Advanced tab is only used once the code has been found in order to decode it There are some parameters that can be set to specify certain expected characteristics about the code and that can help finding and reading codes that deviate from the learned code Maximum Skew Minimum Border Integrity Minimum Quiet Zone Integrity and Maximum Axial Non uniformity Again for a description of these parameters refer to the Intellect Help F
132. ject in bright background That object is considered a dark feature Likewise a light feature is defined by a transition from dark to bright followed by a transition from bright to dark The Vision Tools basically analyze the image and determine where the pixel graph intersects the threshold line edges then group those edges to define features Figure 27 shows a FeatureCount Vision Tool and its pixel graph It can be observed that the Tool crosses four dark regions and five light regions 3 5b Position Along Graph Contrast 78 0 Features MEN ES Figure27 FeatureCount Vision Tool and its pixel graph This is reflected in the pixel graph where four groups of pixels can be identified below threshold and five above threshold These groups of pixels represent the features As the pixel graph shows this Vision Tool is finding nine features four dark features and five light features Depending on the application different approaches can be taken The user can select which features to count If the user selected to count only the dark features the Tool would report four features instead of nine Likewise if light features were selected five features would be reported The default option used in this example is to count both light and dark features If the image to be inspected is not as good as the one in Figure 27 the user may use some options that will make the Vision Tool less susceptible to noise The first option to handle n
133. l Character Verification One Dimensional Barcode Reader The 1D Barcode reader consists of two types of Vision Tools a line Vision Tool arc or straight and an area based Vision Tool The types of barcode that can be read are Interleaved 2 of 5 USS 128 USS 39 Code 39 UPC EAN found on most consumer products Codabar Code 93 POSTNET PLANET PharmaCode BC412 PDF417 Micro PDF417 RSS 14 regular truncated stacked and stacked omnidirectional RSS Limited RSS Expanded regular and stacked RSS 14 Composite RSS Limited Composite RSS Expanded Composite UPC EAN Composite and UCC EAN 128 Composite Note some o f these codes can only be read with the area based reader The line Vision Tool arc or straight must be drawn through the barcode Both versions of the Vision Tool have an extra option to include sub pixel calculation making it more powerful when the image quality is not the best and the line reader crosses the barcode at an angle other than 09 or 459 This option makes the Vision Tool more reliable and the impact on processing times is negligible so it should be used almost every time the above conditions exist The Vision Tool can be programmed to auto detect the type of barcode if the code is one of the first eight codes mentioned above being read or to always search for a specific type of barcode The automatic option adds some processing time and should be used only if the barcode type is unknown The second option can be
134. l I O and Power Cable sold separately Certifications C certified 13 Summary of Image Sensor nformation Table 1 DVT Vision Sensor Information Description CCD Size min Resolution lens format DVT 515 Low Cost Grayscale CMOS All tools except Readers 640x480 CMOS 3 8x2 88mm mm 1 4 DVT 535 Grayscale CCD 640x480 4 8x3 6 mm 1 3 DVT 545 High Speed Grayscale CCD 640x480 4 8x3 6 mm 1 3 DVT 542C High Speed Color CCD 640x480 3 2x2 4mm 1 4 DVT 550 Highest Speed Grayscale CCD 640x480 4 8x3 6 mm 1 35 High Speed High Resolution Grayscale CCD 1280x1024 6 4x4 8 mm 1 25 DVT 554C High Speed High Resolution Color CCD 1280x1024 6 4x4 8 mm 1 2 DVT XS Extreme Scanner DVT LS Linescan Spectral Sensor 550 based High Speed Camera Reader 1D Codes 2D Codes OCR High Speed High Resolution Grayscale CCD Spectrum analyzer for visible and near IR wavelengths 640x480 2048x1 640x480 4 8x3 6 mm 1 3 14 3mmx7 0um 1 In RAM memory is where all processing is done At all points in time almost all data including all products reside in RAM 2 In flash memory is where data that needs to be persistent will not be lost upon power down and power up is stored It is difficult to estimate the number of Products or Vision Tools that can be stored in a particular Vi
135. l calculations based on information from the measurement Vision Tools 68 e Identification Identifies the part based on multiple learned models using either blob properties or color properties e Readers Perform readings of 1D and 2D codes as well as OCR Optical Character Recognition They can be used for recognition verification and in some cases for grading e Color Pixel Counting Color matching tools Learn colors and determine their presence in subsequent images e Defect Detection Learn a model and then verify that the model is present in subsequent images if the image does not match the model it reports the amount of error e Color Monitoring Ultra precise color verification tools e Script Programmable tool that can access other Vision Tools for data gathering etc e Spectrograph Available in the DVT Spectral Sensor this Vision Tool analyzes the full spectrum of a part or light source and can compare it against a list of previously learned spectrums Preprocessing Vision Tool The Preprocessing Vision Tool category contains Vision Tools that alter the image in some way to help the other inspection Vision Tools accomplish their tasks most effectively In general the preprocessing Vision Tools reduce background noise increase edge or foreground contrast or move image pixels around Below is a list of filters in the Preprocessing Vision Tool The Filter Vision Tools use powerful preprocessing algorithms to mani
136. l finds the number of instances of a pattern in an image e Pixel Counting Vision Tool These Vision Tools count the number of pixels in a given region of the image that meet an intensity threshold or color criteria With the exception of Object Locate and Pattern Matching the classification of pixels as bright or dark is based on a user defined threshold For details refer to section Threshold on page 41 EdgeCounting Count along a Line Vision Tools The Count along a Line Vision Tool in Edge Counting mode is designed to detect and count transitions between bright and dark pixels or above and below a threshold The Vision Tool basically analyzes the image and determines where the pixel graph intersects the threshold line Those intersections determine an edge and the user can select the type of edge to locate bright to dark dark to bright or either edge Figure 26 shows the Count along a Line Vision Tool and its pixel graph MPixel Graph Sens BEIR a T z E a Position Along Graph Contrast 71 0 Edges m PASS Figure 26 Count along a Line Vision Tool and its pixel graph The Vision Tool starts on the bright area high intensity and then goes into the dark area low intensity In this case the shape of the Vision Tool is a horizontal line and the direction of scanning is from left to right as indicated by the arrowhead at the right end of the Vision Tool From the pixel graph the user can 5
137. l for each pixel in the region of interest After the calibration is done it will be used by all Spectrograph Vision Tools For more information on this procedure refer to the Intellect help file Auto Calibrate With He 10 Lamp is used in manufacturing with a known lamp Product Parameters The next hierarchical level inside Vision Sensors is the Product Level At the product level we have independent subsystems that are responsible for specific inspections These subsystems are called products All the products in a system use a common set of system parameters as discussed before Since every product is responsible for a specific inspection products need to have control over the imaging process That is why parameters such as illumination image window and exposure time are Product Level parameters Exposure Time Exposure time refers to the time that the electronic shuttering mechanism exposes the image acquiring device to light The longer the exposure time the more light enters the device Three factors will determine the exposure time you set for an inspection e The overall speed of the parts For high speed parts short exposure times are recommended to minimize blur in the images e The overall inspection rate parts per minute In situations where the overall part rate is high exposure time should be minimized to optimize the inspection 34 e The available light Brighter lighting fixtures enable shorter exposure time
138. l need to be the same and the last two can be different Below are some key terms related to subnetting Physical Segment A Physical Segment or subnet is a portion of the network that can receive a broadcast packet All computers within a specified Physical Segment will share a common Network ID Physical Segments are separated by routers because routers cannot forward broadcast packets they can however traverse hubs switches and bridges COGNEX 115 Network ID The Network ID is the part of an IP address that is common to all computers on a specified physical segment The Network ID is equivalent to the area code of a phone number Host ID The Host ID is the part of an IP address that uniquely identifies the device on a specified physical segment The Host ID is equivalent to the phone number Default Gateway A Default Gateway is typically a router that provides a route between two Physical Segments It does not forward broadcast packets So if your Vision Sensor resides in one Physical Segment and your PC resides in another Physical Segment then you will need to setup a Default Gateway to provide a route between the two Physical Segments You would then need to setup up your Vision Sensor and your PC to point to that Default Gateway Specifying a Default Gateway is not required especially if both your Vision Sensor and your PC reside on the same subnet Subnet Mask SNM A Subnet Mask is the second element required in
139. le shows the effect of masking the backlight Masking simply means covering the areas not used or the areas farther away from the edges of the part This will make the edges of the part appear sharper transitions of 3 4 pixels thus making the measurements more precise When there is part movement and the light cannot be masked a collimated light should be used this is shown in the third image The collimator filters the light so that only rays perpendicular to the surface of the light source get to the Vision Sensor causing a similar effect as masking the light m a ii imi STANDARD BACKLIGHT MASKED BACKLIGHT COLLIMATED BACKLIGHT Figure 62 Examples of the use of masks or collimators to enhance part edges when using backlight Another important consideration for obtaining precise measurements is to avoid altering the intensity levels in the image There should be no saturated pixels pixels reporting 100 intensity level Lensing The type of lens used for measurement applications should minimize lens or barrel distortion The best choice is to use telecentric lenses These lenses minimize distortion and perspective error Using a telecentric lens the part size and shape should not vary if it moves within the FOV or even farther and closer to the lens This type of lens can get very expensive as the part size increases An inexpensive alternative consists of zero dist
140. level the user can change parameters that affect a specific inspection such as illumination Essentially a product is directly associated with an inspection so product parameters affect only one of the inspections that the Vision Sensor is performing Finally at the Tool level the user can set some Tool parameters Each Tool performs part of an inspection here is where all the pieces of every inspection are defined Vision Tools are associated with inspection tasks In order to illustrate this functionality let us work with an example The part in Figure 9 needs to be inspected First we need to verify that the drillings on the left end are vertically centered a certain distance apart and of a certain radius After that we need to verify that the label on the right end is centered aligned and that it contains the correct code Finally the specific data from every inspection has to be sent out of the Vision Sensor using Modbus communications The existence of products inside Vision Sensors simplifies this task The inspections can be separated into two groups those that take place on the left end of the part and those that take place on the right end of the part This will allow the user to trigger the Vision Sensor twice as the part moves in a conveyor from left to right The first trigger would occur when the left end is in front of the Vision Sensor and the second one when the right end is in front of the Vision Sensor 28 CY
141. llect are defined as areas of connected pixels of similar intensity Blob Counting is the fastest of the Count in Area Vision Tools but is the least tolerant of intensity changes and noise The Vision Tool in Blob Counting mode analyzes the image and isolates the blobs based on user options threshold level and type of blob to locate There are several intensity based threshold options For an explanation of these options refer to the section on thresholds Once the blobs are located the Vision Tool preprocessing options Erode Dilate Close and Open can be performed to eliminate some noise in the image If the image requires more dedicated processing options the user can reference dedicated PreProcessing Filter Vision Tools to help further condition the image before the Vision Tool inspects it When the image contains noise the number of blobs reported by the Vision Tool may be affected by it When that happens the Vision Tool becomes less reliable and the processing time for the Vision Tool 60 increases due to the extra blobs being processed In order to overcome this type of situation the user can limit the blob size By doing this blobs caused by noise usually very small can be filtered out of the Vision Tool Using this size feature saves processing time since unwanted blobs are filtered out before any heavy computation is performed on the blobs This Vision Tool has a very specific image marking White corresponds to the learned blob
142. lumns and 480 rows of pixels for a total of over 300 000 pixels For high resolution systems the image contains 1280 columns and 1024 rows of pixels for a total of over 1 3 million pixels Every pixel in the image can be considered a source of information so from a standard resolution image the system obtains over 300 000 data points For grayscale systems every pixel provides a numerical value from 0 to 255 which is normalized to values from 0 to 100 This value is the intensity level of that pixel An intensity value of 0 corresponds to pure black an intensity value of 100 corresponds to pure white and the values in between correspond to 99 different shades of gray For color systems every pixel provides 3 different intensity values one for red one for blue and one for green These three values make up the RGB content of that pixel Virtually any color can be represented by using the appropriate coefficient for the base colors Red Green and Blue Using this information Vision Sensors inspect images to provide the user with feedback regarding the presence or absence of a part flaw detection code reading and or verification etc What is a DVT Vision Sensor The DVT Vision Sensor is your hardware tool for assuring quality in manufacturing gathering data and providing information to all levels of your enterprise This information might take the form of device level data such as inspection values being sent to a PLC or process level Stat
143. n a Stop button and a Record button The Play Button is for the user interface The fact that the user interface gets images from the Vision Sensor does not mean that the Vision Sensor is inspecting them The only indication that we have of that is the availability of the inspection results from the Vision Sensor and the control the user has over this process is the Run Stop Inspections button If this is enabled the Vision Sensor is inspecting images which means that it is making the output signals available Table 6 summarizes the different cases Table 6 Effects of User Interface Play Mode User Interface Play Mode PLAY OFF Active updates images Not Available STOP OFF Inactive stopped Not Available PLAY ON Active updates images Available STOP ON Inactive stopped Available Inspection Real Time Feedback Outputs from the Mode to user interface Vision Sensor The user should understand the differences between these two options in order to avoid incorrect configurations The main reason for the independence between these two functions is that the Vision Sensor is a stand alone System It does not need a user interface connected to it in order to inspect images so it must not rely on user interface modes to produce inspection results Likewise the user does not have to rely on the Vision Sensor running inspections to see images and it does not have to stop the Vision Sensor from inspecting to observe
144. n larger than the learn area rectangle To change the Algorithm used by the Vision Tool change the Select task on the Options page of the Vision Tool Parameters Blob Locate The Blob Area Position Vision Tool uses standard and advanced thresholding and automatic parameter setting to find the location of an object based on connected areas of similar intensity pixels It is the quickest of the area based position Vision Tools A Selection editor makes setting blob parameters for the desired object easy This Vision Tool uses the same principles as the Count in Area Vision Tool in Blob Counting mode except the Positioning Vision Tool limits the number of found Blob to one Object Locate The Object Locate Vision Tool uses advanced edge extraction and analysis to locate an object any where within a search area It can locate both whole objects as well as features associated with the object It can also find partial occluded and touching objects It is insensitive to non uniform lighting and low illumination An Object Model editor makes manipulation of the trained object to locate easy This Vision Tool uses the same principles as the Count in Area Vision Tool in Object Locate mode except the Positioning Vision Tool limits the number of found Objects to one There is also a First Match Best Match slider in this mode which is set to First Match by default The more you move the slider to the right the more model segments and algorithms i
145. nd a number of options Each one corresponds to a different model of Vision Sensor The selection of emulator depends on the Vision Sensor that the user needs When the user selects to connect to an Emulator a new Windows application launches in the background The basic steps to work with the Emulator are e Create a backup copy of the system file or product file that resides in the Vision Sensor This step is needed only if the user needs to work on the setup of a Vision Sensor A product file contains all the product parameters specific for every inspection whereas the system file contains all the parameters in the System e Record some images from the Vision Sensor Using the record option the user can setup Intellect to record images imported from the Vision Sensor to the computer hard drive Then when Intellect connects to the Emulator the image sequence can be loaded into the Emulator and the user can cycle through those images This step is optional as the user may already have an image sequence to work with e Start Intellect and connect to the Emulator Choose the Emulator that corresponds to the Vision Sensor used e Perform changes to the system product files as needed The Emulator supports any type of changes the user can add or delete Vision Tools and products set up communications etc The 52 only changes that are not reflected are changes that relate to physical setup such as exposure time illumination etc becau
146. ng Vision Tools need to find it in the image In this case the part shifted up left and rotated counterclockwise q Figure 59 Consecutive images of parts to be inspected The image on the left shows a part in the original position whereas the one on the right shows why positioning Vision Tools are needed The procedure in this case would be to find the vertical displacement the one that changed the most first Then the horizontal displacement and only then determine the rotation The diagram in Figure 60 illustrates the process 94 Positioning Positioning Vision Tool Vision Tool Vertical Horizontal Positioning Vision Tool Rotation Inspection Inspection Inspection Vision Tool Vision Tool Vision Tool Figure 60 Method for passing references The Vision Tool detecting vertical movement finds the change in position in the Y direction Then the Vision Tool tracking changes in the horizontal position uses that information to look for the part in the upper region of the image Once it finds the part it automatically records the change it detected plus the change obtained from the other Vision Tool and passes both as a position reference to the Vision Tool detecting rotation This Vision Tool shifts up and to the left to analyze the rotation in the right location and adds it to the chain of position references When the inspection Vision Tools request information from this one they obtain the changes in p
147. nsor Hardware Emulator The DVT Vision Sensor Hardware Emulator acts like a Vision Sensor but it is a software application that runs on your PC When the emulator application is running the Intellect user interface can connect to the emulator just like a connection to a Vision Sensor Actually Intellect does not recognize a difference between the actual Vision Sensor and the Emulator The main uses for the Emulator are e Education Training With only a PC users can run the emulator application with Intellect and practice using the tools to learn how Intellect operates e Off line Setup Take development of Product files off of the factory floor Use the emulator to continue setup work on Products even after you ve walked away from the machine e Troubleshoot Reliability Problems Is your Vision Sensor rejecting too many good parts or passing flawed parts Save a batch of the images and work off line to find the problem and then perform the necessary changes to improve the inspection and reload the product file to the Vision Sensor e Demonstrations Show the power of Intellect without the Vision Sensor hardware present Intellect s functionality is opened up only after a connection is established to a Vision Sensor or to the Hardware Emulator When the application starts the Network Explorer Manager is opened Users may opt to connect to a Vision Sensor hardware device via Ethernet or to the Emulator Under Emulator the user will fi
148. ognex Return of this registration card activates your Warranty Connecting to the DVT Vision Sensor The DVT Vision Sensors can use Ethernet and the TCP IP and UDP IP communication protocols This section outlines how to establish communications with the Vision Sensor In order to communicate with a Vision Sensor you will need the following e PC A Pentium class PC with the following hardware and software o Windows Operating System Windows XP or 2000 Windows 2000 or a more recent release is recommended o Intellect Software DVT s Intellect User Interface o Ethernet Network Card 10 100 megabit Ethernet card The Ethernet card s appropriate drivers should be installed and the TCP IP communications network protocol should be installed and setup 16 o Ethernet Switch Hub Full Duplex 10 100 megabit Ethernet Switch is necessary for connecting multiple DVT Vision Sensors in a network o Ethernet Cable Category 5 Ethernet Cable with RJ 45 connectors Note a cross over Ethernet cable should be used when connecting directly to a single Vision Sensor that does not have a 5x5 part number The RJ 45 connection on your DVT Vision Sensor is designed to communicate between the Vision Sensor and a PC running Intellect To do this the PC must have an Ethernet network card running the TCP IP protocol Figure 4 shows where the connectors are located in the Vision Sensor Ethernet Connector Legend Series Figure 4 For the DVT Vi
149. oise is to expand the Scan Line Width which works the same way as in Edge Counting mode explained before The second option is a new capability that is unique to Vision Tools that find count features It consists of setting a minimum and maximum feature sizes and the noise filter When this option is used the only features that are counted are the ones whose size falls within a specified range The Noise Size filter is use to disregard small noise pixels Figure 28 shows a sample image with a FeatureCount Vision Tool in it and a pixel graph The Vision Tool is trying to detect the presence of the dark mark but the dark dot on the outside is another feature According to the pixel graph more than one dark feature should be found However it can also be observed that whereas the 58 size of the feature to be located is about 80 pixels the rest of the features do not exceed 20 pixels in size The mouse can be hovered over the different features on the graph to get their individual lengths Position Along Graph Contrast MEDEN Features BER PASS Figure28 Filtration of noise using feature size In this case the user can select a minimum feature size of fifty pixels and only one dark feature will be reported by the Tool This makes the Vision Tool less susceptible to noise making the inspection more reliable The Vision Tool in this mode can be set to pass or fail based on maximum feature count minimum feature count and minimum con
150. olor system It consists of a color CCD of 640 by 480 pixels which makes the Vision Sensor the best choice for most color applications This vision sensor has 3X the processing speed of the DVT 515 DVT 550 Sensor 6X fastest DVT vision sensor available It offers grayscale CCD imaging at 640 by 480 resolution and a high speed DSP chip This camera has 6X the processing speed of the DVT 515 DVT 554 Sensor 6X high speed high resolution system It combines a high resolution CCD 1280 by 1024 pixels with a high speed DSP processor This Vision Sensor can detect very small pinholes stains streaks scratches bubbles and other minute details that normally go undetected by other smart cameras and sensors This camera has 6X the processing speed of the DVT 515 DVT 554C Sensor 6X high speed high resolution color system It uses a color CCD with a resolution of 1280 by 1024 pixels and adds color recognition in all major color modes and spaces found in the factory environment including RGB Optical Density CMY CIE LAB AE and CIE LCH AEcmc This camera has 6X the processing speed of the DVT 515 Every DVT Vision Sensor includes the Intellect software to set up inspections on part presence absence positioning defect detection precise measurement 1D and 2D code readers OCR Color can be used for grayscale levels in monochrome systems and programmable tools to accommodate user needs Figure 1 shows the DVT 535 Vision Sensor Figur
151. on has been completed the system can be triggered for an inspection Product Selection can also be performed over the Ethernet port using a variety of methods These are explained in the Help Files System Graphs System graphs help users troubleshoot systems as well as gather statistical data about the inspections The graphs available at the System level are Inspection Statistics Inspection Times and Digital I O These features are part of the Intellect user interface they do not reside in the Vision Sensor The inspection Statistics graph is particularly useful for troubleshooting This graph keeps count of total inspections inspections that timed out the inspection did not complete in a certain amount of time and inspections that could not be taken when trigger was received The last type of count refers to two cases resource conflict the Vision Sensor is triggered while it is acquiring an image and missed count the Vision Sensor was triggered while the image buffer was full so the trigger was ignored These parameters help users determine when there might be a timing issue with the inspections Figure 13 shows an Inspection Statistics Graph 38 RE lh specion Statistics aa History Sweep Inspection Count mz Conflict Count Missed Count Time Out Count Figure 13 Inspection Statistics Graph The Inspection Times graph is a very important graph It shows how much time every inspection takes showing
152. one unit that runs the firmware All DVT Vision Sensors arrive from the factory with Intellect firmware installed This step should not be necessary unless reinstalling or upgrading firmware Before upgrading start Intellect and click Help About to verify the version of the software being used 1 Start Intellect The Network Explorer window come up 2 Select Network Neighborhood This will search your local network for DVT Vision Sensors COGNEX 117 Y Network Explorer la Network Explorer G actions gt N E ae Name Network Neighborhood Gard 3 rd 3 sandip 3 Emulators 73 Favorites 73 Ethernet Adapters Highlight the appropriate sensor by choosing the system with the matching serial number and DYT SmartImage S IE DVT SmartImage 5 E SmartLink E George s 530 DVT Smart Camera DYT Smart Camera E saos DVT Smart Camera IE phits 510 3 demoRoom 510 DYT Smart Camera B EAngeli 540 daves_542C B Greg 542c Status Group DIAGNOSTICS Diagnostics E nicks 544 lt Up IP Address 192 168 2 26 192 168 2 113 192 168 2 82 192 168 0 203 192 168 2 145 192 168 2 107 192 168 2 163 192 168 2 181 192 168 266 192 168 286 192 168 2 238 192 168 3 9 192 168 2 84 192 168 2 48 169 254 152 67 192 168 2 33 IP Mask 255 255 0 0 255 255 0 0 255 255 0 0 255 255 128 0 255 255 0 0 255 255 0 0 255 255 0 0 255 255 248 0 255 255 248 0 255 255 0 0 255 25
153. or Extreme Scanner and the DVT SC DVT Spectral Camera Itthen moves on to how to install the software Intellect User Interface walks the user through the process of setting up the Vision Sensor and explains how to establish communications with it The chapter ends with a brief description of the new features of Intellect 1 3 and a guide to other resources What is Machine Vision Machine vision in layman s terms is exactly that It can be defined as machines with their own set of eyes Using their vision machines inspect products for defects by detecting the presence or absence of parts taking measurements reading codes etc How it works may seem rather complicated at first glance However with a little help from basic optics it is not The machine s eye mainly looks for changes in contrast and uses a 2 dimensional plane to do so Our Vision Tools tell the camera the machine s eye how to evaluate changes in contrast and in what direction to evaluate them The camera then collects this information from the image and evaluates it following the user defined rules Because the camera s actions are so dependent upon that change in contrast it is imperative that you adjust your lighting such that the camera or machine can get a consistent and close look at the factory product Imaging and Pixels Every image from the Vision Sensor can be considered an array of pixels For standard resolution systems the image consists of 640 co
154. ortion lenses Most lens manufacturers carry a number of this type of lenses Positioning Robotics Applications Applications requiring the position of an object to be obtained involve Vision Tools that can generate the location of a part feature and conversion from Image coordinates to Robot Real World coordinates Vision Tools used for these applications are generally Measurement Math Vision Tools with a Coordinate Transformation Vision Tool for converting to real world coordinates Object Blob and Pattern locating using an Area Positioning Vision Tool can also be used if general position location is desired This Vision 97 Tool requires more processing time because they scan entire areas searching for objects A Coordinate Transformation can be used both to change pixel coordinates to robot coordinates and to correct for lens distortion both require previous calibration The second correction can be minimized by using a better type of lens Setting up a Coordinate Transformation A coordinate transformation establishes a relationship between the Vision Sensor image pixels and the plane of the real world that the Vision Sensor is imaging This allows positions and measurements to be reported in the robot space A coordinate transformation is established at the system level and can be used by any products in the Vision Sensor There are three methods to generate a coordinate transformation Standard DVT Grid Custom Grid and Script Based Usin
155. ose rules are related to the specific functionality of the Vision Tool That is for measurement Vision Tools the condition would be based on maximum and minimum size for the barcode reader it would be set based on a matching code etc However there is an option that is common to most Vision Tools Minimum Contrast The option of Minimum contrast should be used when a dynamic type of threshold is being used The use of this option will be illustrated with an example suppose the user selects Percent of Path Contrast as the method for calculation of a threshold The Vision Tool as explained before will determine the intensity levels of the brightest and the darkest pixel and based on those numbers it will compute a threshold level This is a very powerful method but what happens when the part is not present Only the background is present so the Vision Tool sees a very low contrast given by the noise in the background Based on this contrast the Vision Tool still computes a threshold for the image Figure 21 shows the pixel graph for a Vision Tool illustrating this case 44 A B Pixel Graph E Show Graph Pixel Graph Ba Ea Show Graph 100 Atel ntenut Ritel ntenalty su 100 Potion Along Graph tel Folton Along Graph Pirels Figure 21 Case where the part being inspected determined by the group of light pixels in the graph on the left is not present in the next image The graph on the right shows that there is still a thr
156. osition generated by all three positioning Vision Tools This method simplifies the setup process because position references are automatically concatenated and the inspection Vision Tools need only reference one of the positioning Vision Tools As mentioned before just one Area Positioning Vision Tool like the Blob ObjectLocate or PatternMatch Vision Tools could have been used but they would have consumed more processing time The Blob Object and Pattern finding algorithms are area based algorithms that is they scan an entire area looking for a shape This process takes more processing time than a line scan like the one performed by line Translation Vision Tools Presence Absence Inspections Presence Absence inspections involve inspecting a part for specific features to make sure the feature is present or absent The locations of the features of interest in a Presence Absence inspection are generally known Many of the Vision Tools within Intellect can be used to inspect for the presence or absence of features of an object Counting Vision Tools are commonly used for presence absence but Measurement Identification Flaw Detection and Position Vision Tools can also be used to determine the presence or absence of a part or feature Each one of these Vision Tools has different advantages and disadvantages Line based Vision Tools like the FeatureCounting and EdgeCounting are the ones that take the least processing time but they are more sensitive
157. p to DVT systems o System Explorer Window This window allows easy and organized access to the following managers and settings Background Scripts Window From this window the user can add delete edit and create background scripts Please refer to the script documentation for information about background scripts Coordinate Systems Opens the system manager to the coordinate system section which allows coordinate transformations to be defined This feature is most often used with robotic and measurement applications Product Manager Opens a listing of all products in the system where the user can rename the products specify the Power On product the Inspect Product and the Selected Product The user can also apply coordinate transforms in this window Retained Images The retained images option allows past failed images to be viewed 49 Communications Settings This option opens the communications manager which is used to set up communications between the Vision Sensor and other industrial devices Communications include digital IO Ethernet TCP IP Modbus etc o System Calibration The calibration dialog allows the Vision Sensor to be calibrated for Sensor Gain FOV balance White Balance and Reflectance o System Administration The system administration section contains information on flash memory security users and licenses It also contains information about image buffers The size of the image buffers is o
158. pplications Subtract Dark Image Subtracts the live image from the stored dark image It is usually used to remove dark current CCD noise Can also be used as image compare Flip Image Always the image to be flipped along an image axis Mainly used when the image is formed with a mirror Measurement Vision Tools Measurement Vision Tools are used to take measurements from the parts being inspected These measurements will be in pixels unless a scale factor or coordinate transformation is performed There are two types of Measurement Vision Tools line based and area based In this case the area based Vision Tools consist of a number of scanning lines That is they collect data from many lines in order to produce a more accurate result Typically each scan line will produce a data point by finding an edge The Vision Tool then uses all those data points to perform calculations e g fit a line or a circle All the Measurement Vision Tools can use gradient based methods for thresholds in addition to the intensity based types When a gradient based threshold is being used sub pixel accuracy can be easily achieved and some advanced Vision Tool parameters become available Edge Width Use Best Edge and Hough Transformation These options make the Vision Tool less sensitive to noise This is how they help the Vision Tool perform the inspection e Edge Width This option lets the user indicate how many pixels determine the edges to be us
159. pulate the pixels of a region or the entire field of view to help enhance the inspection of other Vision Tools They can be a very powerful tool to help reduce background noise enhance edges filter colors and other operations The operations can result in a more robust inspection at the expense of inspection time Since the filtering algorithms are often complex and are applied to an area they will increase the overall inspection time To use a filter Vision Tool draw the preprocessing Vision Tool in the area in which your inspection Vision Tools will be inspecting and select the desired preprocessing operation in the Options dialog In order for the other inspection Vision Tools to use this filter the inspection Vision Tool must reference the filter Vision Tool in the General Section of its Vision Tool parameter page in the image reference dropdown The filter Vision Tool rectangle must encompass the entire inspection Vision Tools shape If it does not or if the inspection Vision Tool move off of the filter Vision Tool then the inspection Vision Tool will truncate the shape in most cases to fit the filtered image or fail with a moved off image failure cause When first drawn the Filter Vision Tool will default to No Filter as the Preprocessor Operation To change the Algorithm used by the Vision Tool change the Preprocessor Operation on the Options page of the Vision Tool Parameters If more than one Preprocessing operation is desired the
160. puts more emphasis of true edge points and less on noise Figure 38 illustrates the use of this option Image a shows the output line calculated with no iterations As the image illustrates the output line is not on the edge because of the imperfection of the part Images b and c show the same Vision Tool after 2 and 5 iterations Image c is the only one that finds the edge of the part regardless of the imperfections that the part presents 71 a No Iterations b 2 iterations C 5 iterations Figure 38 Use of the number of iterations to overcome imperfections noise in the part Note scan lines show for illustration purposes only e The Outlier Distance option is used after the iterations and it discards points that are more than a user defined number of pixels away from the output line circle This option helps find the right edge of the part giving a more accurate result There are five main measurements that the Vision Tools can compute thicknesses radius straightness roundness and concentricity Thickness measurements can be performed using a line or an area Vision Tool In both cases the Vision Tool can scan inside out or outside in just like using a caliper The scanning lines start scanning from the ends of the Vision Tool or from the center until they find the specified characteristic This characteristic could be a peak value in the gradient graph when using gradient computation or a specific type of edg
161. r 1280 by 1024 The naming convention should be followed as well COGNEX 108 Appendix B Basic TCP IP Setup In this section we will step through setting up the TCP IP protocol on a PC TCP IP stands for Transmission Control Protocol Internet Protocol and is based on identifying elements on a network by unique numbers called IP numbers We will assign our PC with one IP number and any Vision Sensor with another There are several methods of connecting PCs and Vision Sensor systems Note that if the PC is already in a network it perhaps is configured properly and does not require a TCP IP setup c For Windows XP and Windows 20009 E Network and Dial up I Connections Click on the Start menu in Windows select Settings then Control Panel Double click on the Network and Dial Up Connections Control Panel icon shown above right To check for the list of installed network components for your network card right click on it and select Properties as shown below If TCP IP is on the list in the corresponding dialog box click Cancel and skip to the Communicating with the Vision Sensor section File Edit View Favorites Tools Advanced Help ff Network and Dial up Connections Address ay Network and Dial up Connections a Make New Connection Integrated NIC Network and Dial up Disable Connections Status Create Shortcut Delete Type LAN Connection Rename Integrated NIC Status
162. r PC You now have a DVT network e For more advanced network configurations you will need to adjust the Sensor Address Mask For a DVT Vision Sensor and PC to communicate they must be on the same sub network This means that the masked portions of the sensor s IP address must be identical to the PC s For example with the default mask of 255 255 255 0 on your Vision Sensor only the fourth portion of the PC s IP address may be different from your Vision Sensor In this example a sensor at 192 168 0 242 can communicate with a PC at 192 168 0 200 but not with a PC at 192 168 1 200 19 The following table summarizes the use of the Sensor Address Mask property with Ethernet networks Table 2 Network Address Configurations Sensor Address Mask Sensor IP Address Valid Sample PC IP Addresses 255 255 255 0 192 168 0 242 192 168 0 200 192 168 0 100 192 168 0 240 192 168 1 200 255 255 0 0 192 168 0 242 192 168 35 67 192 168 222 35 192 25 1 200 255 0 0 0 192 168 0 242 192 222 22 242 192 0 1 45 Warning Whenever connecting a node to an existing network please exercise extreme caution Connecting a DVT Vision Sensor to a network without the Network Administrator s knowledge is not recommended 20 DVT Vision Sensor Hardware Setup In this section physical connections to the DVT Vision Sensor are explained This includes powering the system connecting the communications cable an
163. r system files loaded in the Vision Sensor In order to do this the Intellect user interface queries the Vision Sensor for images and reproduces in the PC what the Vision Sensor does in its internal memory with those images Intellect User I nterface The Intellect User Interface is a Microsoft Windows application used for the configuration of Vision Tools The main areas of the interface are the main menu the toolbars the Vision Tool toolbox the Video Display the result table the properties window and the status bar Figure 25 shows a screen capture of the Intellect user interface highlighting these areas i DVT Intellect 1 3 DVT Vision Sensor DVT le Edi E Prodi Tool Wind Main Menu File Edit View Image System Product Tool Windd Toolbars System UM c E 2 PI Image a M B p K 4 XQ we O e Tol Ton 3 Product Product D X x E 8300 3 Video Display C Color Wires Wires001 bmp felix Properties mix Vision Tool E 18 Toolbox Video Display 9 Inspection Trigger Properties v General Properties Counting Type Inspection Trigger Measurement Name Inspection Trigger Basic Settings ES Measure along Line E Trigger Soi ES Measure in Area i Trigger Perl P rope rti es Measure in Circle Sane Wi ndow B ath Pi Ii Me with Print least UE ninl Feedback Identification a P Timing ms Readers Flaw Detection Script Application Specific
164. r to select one of the colors in the learned list The name of the ClosestColor must match the selected color or the Vision Tool will fail Foreground Scripts Script Vision Tools A foreground Script is a programmable tool that allows the user to write a short program with access to data from other Vision Tools This program which uses a very common syntax similar to Java C and C is always part of a product and is executed when that product is used to inspect an image That is why they are called Script Vision Tools Script Vision Tools can Be set to pass or fail based on certain conditions except that the user defines those conditions There is not a predefined set of rules because of the versatility of this type of Vision Tool Access data from other Vision Tools and draw a conclusion pass fail based on data from several Vision Tools Perform mathematical calculations using built in functions or by letting the user program new functionality Access registers in memory to interchange data between different products with background scripts or even with external devices For more information documentation about all the specific functions and examples about Script Vision Tools please refer to the script documentation and Intellect help files 87 Spectrograph Vision Tool The Spectrograph Vision Tool is a Vision Tool designed to work with a special sensor in the DVT Vision System family the DVT Spectral Camera Figure 53
165. relate to faster updates of images in the Intellect user interface e Available Space Intellect requires a minimum 100 MB hard disk space e Ethernet Card 10 100 megabit Ethernet card with integrated RJ 45 jack Integrated Ethernet is recommended Installing the Intellect User Interface The steps to follow are e Insert the Intellect CD The Intellect installation should automatically start However if the CD does not automatically run follow these steps e From the Start menu choose Run e Type D setup exe substitute the appropriate drive letter of your CD ROM drive for D and press Enter e Follow the installation instructions on screen After installation Intellect will reside in the C Program Files Cognex DVT intellect1x directory assuming the user accepts the default selection for directory location The Intellect User Interface file is named intellect exe and firmware files end with a numerical extension indicating the DVT series number of 5x5 54x or 55x the hardware platform with which they are associated For example the firmware file for Intellect 1 3 release 1 for a DVT 515 sensor is named intellect131 5x5 These firmware files contain the code that needs to be downloaded to the Vision Sensor They are the part of Intellect that resides in the Vision Sensor where all the calculations take place Please take a moment to fill out the registration card included with this manual and return to C
166. ring light It uses an external white light that offers a very high intensity minimizing the exposure time Spectral Camera Figure 2 DVT Spectral Sensor DVT Vision Sensor Specifications Size 112mm x 60mm x 30mm not including spectrograph for the DVT Spectral Sensor which adds an additional 122mm to the 30mm dimension or a lens an additional 50mm cable clearance added to Mounting Four M4 threaded holes on back of unit 7 9mm depth 12 Weight 170g 6 oz without lens Power Requirements A regulated and isolated 24 V DC power supply is needed sold separately 210mA for the 520 and 530 systems a minimum 5W or 300mA for the rest of the Legend Series a minimum of 7 5 W If DVT LED array lights are used the power supply must provide an additional 30W required per array Operating Temperatures 0 45 C 32 113 F non condensing environment Maximum 50 C 122 F Electronic Shuttering 10us 1s exposure times Optics CS mount standard C mount capable with an adapter sold separately External Ports Keyed 10 pin RJ 45 connector Power and Digital I O RJ 45 10 100 megabit Ethernet communications TCP IP protocol connector Digital I O 24 Volts DC regulated 8 configurable inputs amp outputs NPN current sinking inputs PNP current sourcing outputs active high signals Inputs can sink up to 1 5mA and outputs can source a maximum of 50mA Warning Users are strongly encouraged to the DVT Digita
167. roach In those cases a background script should be used From a background script the user can create a Modbus transfer object which can perform a number of standard Modbus functions as specified in the open Modbus protocol For more information about this see the script documentation Ethernet Terminal Controller ETC The Ethernet Terminal Controller ETC allows the user to set up different Ethernet configurations for communication using the TCP protocol This converts the Vision Sensor into a TCP server or client Depending on the application the user can select the Vision Sensor to be a client connect to another device or a Server expect a connection from other devices In both cases the connection will be established using a user defined port Using this connection the following drivers can be used to communicate with different devices e System Driver Supplies an additional port for the data exchange at the system level that normally happens on port 3246 port 5000 for older systems e DataLink Driver Supplies an additional port for the data exchange from DataLink that normally happens on port 3247 port 5001 for older systems e Robotic Drivers for Motoman and ABB Robots The user can configure the Vision Sensor up as either a TCP IP server or client and specify the preferred port The user can also set the Ethernet port for communication as well as the type of communications driver to use on the port from this selection T
168. rom each other in the number of features they extract from a character High resolution mode extracts about 1600 features from the character medium extracts about 800 and low extracts 200 The selection of medium or low resolution reduces the processing time at the expense of reliability in the identification of the characters It should be mentioned that the different modes apply only to comparisons That is the characters are always learned in high resolution mode to make the comparisons more reliable The second option to reduce the processing time increases reliability as well and is called character fielding Character fielding allows the user to specify the type of character to look for in the different positions of the string to be read When the application allows for it the user can specify what type of character to 81 look for in every position of the string code to be read For example if a particular code consists of two upper case letters and two numbers the user could specify that in the Vision Tool parameters This will tell the algorithm to check the first two characters against all 26 upper case letters and the last two characters against all 10 numerical digits This reduces the processing time by reducing the number of comparisons and makes it more reliable ex number 8 will not be confused with letter B because it is not being compared against it Another powerful feature of this Vision Tool is that it can search for charac
169. rovide power isolation when working with devices that are using a separate power supply Features Power Jack Purpose Included for the use of a 24V 1 42 A wall mount power supply It should only be used for demonstration and laboratory purposes Power Terminals There are three main power terminals V GND Shield providing connections for an industrial power supply There are two additional pairs of V and GND terminals Non isolated I O Terminals Located on the right side of the board there are screw down terminals for the 8 I O lines available on the DVT Vision Sensors There is an extra terminal connected to I O line 8 intended to provide one more output for a strobe illumination This output will be activated during image exposure only if it is configured in Intellect as the Strobe output Isolated I O Terminals Located on the left side of the board these are to be used in combination with isolation modules Isolation modules slots There are 8 screw down slots for input or output isolation modules 15 pin high density D sub This provides connection to the I O and power lines of the DVT COGNEX 121 plug DVT vision systems which use a 10 pin keyed RJ 45 port COGNEX ISOLATION TERMINALS REQUIRE ISOLATION MODULES SEAN i AON i Port 2 i O O O o O s E L1 o O ISOLATION
170. rs The Vision Tool can learn merge and export the colors to other Vision Tools to be used as a threshold When the Color Pixel Counting Vision Tool is being used just to export the colors it learned it might not be necessary for the system to keep processing the Vision Tool in every inspection The user can disable the Vision Tool so that it can stay around but not consume processing time When the option Disable Inspection under the Training tab is activated the Vision Tool is only processed and inspected when a digital relearn signal is received and new colors are to be learned Color Monitoring The Color Monitoring Vision Tool in the Flaw Detection group is another type of Color Vision Tool It is a much more precise Vision Tool than the Pixel Counting Vision Tool This Vision Tool can differentiate approximately 16 7 million colors whereas the Color Pixel Counting Vision Tool can only discern about 65000 colors As a result the Vision Tool is used mostly to identify different colors when they are very similar This Vision Tool reports the difference between colors If many colors have been learned the Vision Tool reports the color difference with respect to the closest color The Vision Tool can be setup to work in the following color spaces e RGB is the default color space Color difference is calculated as the Euclidian distance between two points If Matte Line is selected distances are measured to the matte line instea
171. ry code is ready for reading Inspection Trigger Turned on to start acquisition of an image for inspection when the system is in external trigger mode Encoder Inputs Used to time inspection triggers based on encoder inputs These are labeled Event Counter and Quadrature Input Digital Relearn Used by Positioning Counting OCR Code readers Spectrograph and Color Vision Tools to automatically relearn or reset Vision Tool parameters Relearning will occur if the Digital Relearn input is held active during the next inspection and the Vision Tool has its Digital Relearn parameter checked External Trigger Mode Set the camera to external trigger mode This means that it will not acquire images unless a trigger signal is sent by an external device Result Acknowledge Informs the camera that the inspections results were received For Inspection Results under Result Type the user specifies how the camera should output its physical signal e g hold last state until next inspection One of the options is to maintain the value until this Ack signal is received This way the user can establish a handshake between the camera and the industrial device communicating with it e g PLC Event Counter This is used when an encoder is connected to the camera to time events based on tick counts rather than absolute time This is particularly useful in the Line Scan system where this signal will be connec
172. se the Emulator works with prerecorded images e Back up the product system file to the PC and restore it to the Vision Sensor For a quick tutorial on this process see Appendix A Emulator tutorial 53 Chapter 3 Vision Tool Reference This chapter explains the main concepts of the Intellect Vision Tools As it was mentioned before Vision Tools are the workers inside Vision Sensors Every type of Vision Tool serves a specific purpose and the combination of the Vision Tool results represents the overall result of the inspection The main groups of Vision Tools are Filters Positioning Counting Measurement Identification Reader Flaw Detection Script and Application Specific Vision Tools Positioning Vision Tools help locate parts to be inspected In most applications this type of Vision Tool becomes the key to a successful setup because they locate the part to be inspected and pass an internal reference to the remaining Vision Tools indicating the location of the part Counting Vision Tools are often used for Presence Absence applications were the application is to detect features Specific Inspection Vision Tools include 1D and 2D code readers OCR readers measurement Tools math tools color Tools identification flaw detection spectrograph for color analysis and programmable Tools 55 Intellect Vision Tools This section contains information on the different Vision Tools contained in Intellect These include Preprocess
173. sesceisessscscesococssessceessscsescssecnsesssaresosssssescesusavesensedensiscanesosstedecess ensooscoonesesss 96 Counting INS HSHITIDI ERR H 96 Measurement Inspections cisccsescccsssssisnccsocotsscesss enesscncssnsstuceessencedencsteuncessadessbatonescesetdessoasssseasssenees scares 96 Techniques for Better SubPixel Measurements essere eene enne enne nnne nennen nre 97 Positioning Robotics Applications 97 Setting up a Coordinate Transformation nete nennen rennen innen e teen ene ennn nenne trennen enne 98 Color Sorting Identification Applications 98 Part Identification PR 98 Lot Code and Data Code Applications 99 OCR utn nae teeth Eu t aM 99 TD Reader ete etie ete ee ete eie cnm e dete ed n ete E ce 99 PA D Reader RERBA EE UMS 99 Chapter 5 DVT Vision Sensor Integration 101 Transferring Data from a DVT Vision Sensor 102 Data Lk qe dei 102 Modbus Ernst up memi tesis ee ee 103 Ethernet Terminal Controller
174. shold that places the threshold at some location between the minimum and maximum intensity values based on the 43 value set by the user This threshold is calculated as follows Threshold I yax Lu X T Ly The 726 represents the threshold percent set by the user Zmax and yy are the maximum and minimum intensity values inside the area that the Vision Tool is set to analyze This option selects a threshold which can adapt itself from image to image dynamic threshold which makes it more robust that any static threshold e Intensity Based Local Difference Method for 1D Reader The local difference method uses a dynamic threshold based on a small sample window This method is used for uneven lighting or very small less than three pixel transition between light and dark This method evaluated the surrounding minimum and maximum intensities to establish an edge Used for 1 Reader Vision Tools e Intensity Based Auto Bimodal This method automatically calculates a single threshold value to use based on the entire histogram Since it uses all the values in the area to calculate the threshold the effects of noise and specular reflections are minimized Auto bimodal thresholding is recommended when there is a distinct foreground and background intensity The threshold is recalculated for each image e Intensity Based Adaptive for OCR Reader The system calculates a specific threshold value for different areas of the image depend
175. sion Sensor the RJ 45 Ethernet port is the port on the right with two indicator LEDs Assigning an IP Address to a Vision Sensor The PC and Vision Sensor communicate using the TCP IP and UDP IP networking protocols TCP IP stands for Transmission Control Protocol Internet Protocol and is based on identifying elements on a network by unique numbers called IP addresses In order for two devices to communicate they must reside on the same Local Area Network LAN be part of the same sub network and have unique IP addresses UDP stands for User Datagram Protocol and is lightweight connectionless and efficient but it does not guarantee successful and error free delivery of data packets This protocol is used within Intellect for browsing the network and finding DVT Vision Sensors All DVT Vision Sensors come with a default IP address which must be changed to a number compatible with both your computer and LAN An IP address is the equivalent to a telephone number The Vision Sensor will assign itself a default IP address You must then re assign a new IP address that is compatible with your local network In other words you must make sure that you have the right phone number to call the Vision Sensor When the Vision Sensor is in Diagnostics mode the user can double click or right click and choose Setup IP Address on it to open the Setup Camera IP Address Wizard which will walk the user through this process and make recommendations as to which
176. sion Sensor even knowing the amount of memory available This is because different Vision Tools occupy a different amount of memory Most Vision Tools that do not require training or learning of a model template font list or other parameters take up less than 5 KB However the exact amount of memory may also depend on the size of the Vision Tool especially for the area based Vision Tools The user can look at the amount of flash memory left in a Vision Sensor in the Product Management dialog box under the Products menu In Intellect flash memory is reclaimed automatically 14 DVT Vision Sensor Dimensions Jar 112 CS Mount 1 00 x 32 TPI 4X M4x 0 7 THD 7 8mm deep HE ae A 60 Without LED Cover 60 With LED Cover Note All Units in mm Figure 3 Schematic of DVT Vision Sensor 15 Installing Intellect Software While it may be very tempting to immediately insert the Intellect CD into your computer please take a moment to ensure that installation will go smoothly The following is a list of requirements necessary for a proper installation of this version of Intellect PC Requirements e 400 MHz Pentium class PC For best results we recommend that you use Windows XP or a more recent version of Windows on your PC However Windows 2000 will work as well NOTE Windows 98 and Windows NT 4 0 will not work with Intellect A minimum of 128 MB RAM will be required A faster processor will directly
177. so the Vision Tool only finds 1 pill In this case the Vision Tool should fail based on the blob count Table 7 Description of Blob Parameters Parameter Description Example Measured from clockwise from 3 o clock Ai lt A2 Angle position Must check Calculate Blob Angles to then select blobs in range S gt B c Position of blob centroid as measured Position from image origin upper left corner Blob 1 142 83 Blob 2 140 96 Must check Calculate Blob Positions to X X5 Yi lt Y2 then select blobs in a certain range Measured in pixels Selecting blobs based Area on area is a very common way to sort Ai lt A2 shapes BB is the width and height of the Bounding BOX rectangle that encloses a blob Measures rotational symmetry of a blob 0 1 scale with most eccentric shapes near a Ld gt Eccentricity 0 very asymmetrical and least eccentric cor AN near 1 very symmetrical Independent of scale A measure of blob density 0 1 scale with least compact shapes near 0 less dense Compactness and most compact near 1 more dense mG O Independent of scale I Measures the total length of all edges Pi lt P2 Perimeter i ERR i around the blob including interior edges Avg Intensity Measures average intensity value of the 9 connected pixels l L lt D 62 The radius in pixels of a shape For non circular blobs this value represents the distance from th
178. ss The first step is to draw a certain shape in the image The available shapes depend on the type of Vision Tool being used and the selected shape 41 depends on the part being inspected The two main categories of Vision Tool shapes are Line Vision Tools and Area Vision Tools Line Vision Tools are mostly used when edges need to be found These types of Vision Tool scan along lines analyzing every pixel along them e Line Segment Allows the user to draw a line at any desired angle e Polyline Allows the creation of a line defined by straight segments used for analysis of very complicated shapes e Circle Draws a circle used for analysis of round or highly symmetric shapes e Ellipse Draws an ellipse designed for cases where a circle is to be analyzed but perspective errors make circles appear as ellipses e Elliptical Arc Circular Arc Draws an incomplete circle used for cases where only part of the ellipse or circular region is to be analyzed It should be noted that even though some lines are closed that is they draw a figure the Vision Tools are line Vision Tools and they only analyze the edges of those figures Only area tools analyze areas NOTE For instructions on how to draw a specific type of Vision Tool select the desired shape and refer to the I ntellect status bar for click by click instructions Area Vision Tools analyze the pixels contained in a specific area of the image That area is determined when th
179. subsequent images As mentioned previously 83 in the counting section if a grayscale system is used the Vision Tool learns a shade of gray and uses it as if it was a color There is not a concept of threshold in this Vision Tool When the Vision Tool is drawn it learns the most dominant color within the learn region and sets a volume around it as shown in Figure 49 The space within which the color is defined can be changed using three parameters Those parameters are e Sigma Factor Changes the size of the space in all three axis in the 3D color space Increasing it will include more similar colors in the volume Decreasing it will make the color selection more specific e Matte Areas Help the user select darker and lighter shades of the same color In the 3D color space the matte line starts at coordinates 0 0 0 and passes through the selected color The darker shades of the color are located between the color and black the lighter shades are located on the other side of the matte line e Highlight Areas Are used to include areas of the color that contain direct reflection of light The areas affected by reflections tend to be white so the highlight line goes from the selected color to white coordinates 100 100 100 Figure 50 illustrates the effects of the use of these parameters the first diagram shows a learned color The color occupies a limited volume in the RGB space The image on the upper right corner shows the effect of
180. sult table with correspond to this Vision Tool The Status Bar the last section of the user interface contains three main sections e Instructions section This is the left side of the bar When the user selects to create a new Vision Tool it displays click by click instructions so the user does not need to remember how to draw every Vision Tool 51 e User section This section is related to the Vision Sensor administrator it shows the username under which the current operator is logged on It will show Guest when no user has logged on e Image information section This part of the toolbar is used in combination with mouse movements When the user moves the pointer over the image being inspected this section of the status bar will show three values for grayscale systems and five values for color systems The first two values in both cases are the X and Y coordinates of the pixel where the pointer is located X coordinates start at zero on the left edge of the image and increase to the right and Y coordinates start at zero on the top edge of the image and increase downwards This section also shows calibrated coordinate system values if available For grayscale systems there is a third value which indicates the intensity of the pixel between 0 and 100 For color systems there are three values instead of an overall intensity value these numbers represent the Red Green and Blue intensity values of the pixel DVT Vision Se
181. t will use for matching If you have a case where the location of the object is not found correctly you can move the slider to the right or increase Minimum Match Score Pattern Match Locate The Pattern Match Vision Tool uses advanced gray scale correlation to locate a pattern anywhere within a search area It locates the position of a learned pattern that translates It finds the pattern with the highest match score based on a gray scale correlation Although it can tolerate some limited rotation it is designed more for finding object in pure translation without rotation If location of a part that rotates is desired then the Object Locate or Blob Positioning Vision Tools are recommended This Vision Tool uses the same principles as the Count in Area Vision Tool in Pattern Match mode except the Positioning Vision Tool limits the number of found Patterns to one Vision Tools used for Specific nspections The next group of Vision Tools is the Specific Inspection Vision Tools set These Vision Tools perform many tasks from very specific inspections to a user defined task programmable These Vision Tools are e Filter Vision Tools The Filter Vision Tools use powerful preprocessing algorithms to manipulate the pixels of a region or the entire field of view to help enhance the inspection of other Vision Tools e Measurement Vision Tools Take measurements from parts for inspection or simply to gather data e Math Tools Perform mathematica
182. ted to either of the two output lines of an encoder to receive the line triggers for image acquisition However it can also be used for other parameters such as specifying a delay after trigger 30 Quadrature Input acquisition This signal is specifically used in combination with Event This is used in the Line Scan system It will be connected to either of the two output lines of an encoder to receive the line triggers for image Counter and will only work if you are using the encoder settings under Physical I O in Quadrature Counting mode Only available for Pin 2 Disable Run Mode Stops the camera from executing inspections This does not necessarily mean that the camera will stop acquiring images if the user interface is in play mode the camera will still take images However it means that the camera will not set any of its outputs User Inputs Inputs 1 32 are used in combination with DVT Scripts and Background Scripts to monitor inputs See the Script Reference Manual for more details and examples In addition to assigning specific functions to the I O pins the user can specify other parameters to ensure that the inputs are correctly read by the system The use of these parameters depends on the hardware device providing the connection to the Vision Sensor These parameters are polarity inversion debounce times and input filtering Polarity inversion is used to change the system lines from active
183. ter hard drive with the name specified by the user and an extension indicating if it is a system file extension dvtisys or a product file extension dvtiprod Step 2 Record images from the Vision Sensor In order to do this the user must select Record gt Recording Setup under the Images menu This dialog box lets the user select the directory where the images are to be saved the name for the images and the number of images to record Setup Recording Properties a Q Image Acquisition Properties Directory C Temp zm La General Properties File Type b 4 Input Properties 0 Filename Prefix leftSide Output Properties Gi General Output First Image Number Image Focus v Image Display Current Image Number 9 LEES Images to Display Sensors To Displa All Images Last Image Number play Passing Only s Local Marking Mode Failed Only wrap to First Image All Images Stop on Fail i Display Sensor Shape Image Quality 1 4 Resolution Transfers True 1 4 Resolution Smoothing True Image Zoom 95 10095 Image Rotation D degrees Cancel Image Palette Gray Scale The user must specify the number of the first image in the sequence the number of the current image the next image to be recorded and the last image to record The last option Wrap to First Image indicates whether to stop on the last image or start overwriting from the first one This will create a number of bitm
184. ters Once the Vision Tool learns some characters it can be set to find one or all of the characters This could be used for position reference for other Vision Tools even for a second OCR Vision Tool Before starting a search the Vision Tool scans the list of trained objects to determine the maximum and minimum height and widths From this it creates a search window that is moved inside of the region of interest When a potential edge of data is found the Vision Tool moves through the font list one object at a time placing a window of the size of that trained object at the location of the potential edge The edge is assumed to be the lower left hand corner of the window As each window is placed a read is made attempting to match whatever is in the window with any trained object If more than one object matches the object with the highest score is returned If no object matches the search window continues from where it was last progressing bottom to top left to right This Vision Tool can be set to pass or fail based on a string to be matched one or more characters not being read and a character being read but with a low score The score represents how well the character matches the learned character Scores range from 0 to 1000 to show how well the character is matched a score of 1000 represents a perfect match 82 Intro to Color Vision Tools The RGB Color Space In order to better understand the functionality of th
185. that every string is fully configurable gives the user the flexibility needed to implement an effective inspection In order to read the data sent out from DataLink the user needs to establish an Ethernet connection using TCP protocol to port 3247 DataLink output can also be sent in XML format XML is becoming the standard for specifying the actual meaning of data In this case the names of the tags and overall format are hard coded Additional meta data is provided beyond what DataLink s regular format provides so as to make parsing easier For example the parameter s name and format int float etc is given as well as the associated Product name To enable this new output format the user should select the XML Output for the output type in the datalink properties page Modbus Transfers A very efficient way to share data among DVT Vision Sensors or between a Vision Sensor and an external device is to perform a Modbus transfer Modbus transfers as implemented in the Intellect user interface take a number of registers from one system and copy those registers into another system Using this simple procedure one Vision Sensor can make a decision based on the result from other Vision Sensors or gather data from other Vision Sensors and send it out to an external device In a Modbus network we have master devices and slave devices Vision Sensors can be enabled to be a Modbus slave which will make the system expect a connection on port
186. these two modes regarding image acquisition play mode and inspection mode Play mode applies to each user interface connected to a Vision Sensor and it is independent of the inspection process so its activation does not require the presence of an inspection product When Real Time Feedback is enabled in a user interface play mode becomes active and the Sensor sends images to be displayed by each program Inspection mode determines whether the Vision Sensor is currently inspecting images or not When inspection mode is active the Vision Sensor sets all configured output signals and sends out any TCP data that the user has set up The activation of inspection mode requires an inspection product If a product is selected as the inspection product and the inspection mode is activated then when the Vision Sensor is triggered it acquires an image and inspects it according to the Vision Tools that the chosen inspection product contains and sets all appropriate outputs Password Protection In order to provide administrators with access control Intellect supports the creation of different user accounts This allows system administrators to give specific control of the system to different users Each user can be given certain access restrictions from simply stopping the inspection mode to editing the parameters of every Vision Tool Administrators can choose which tasks each user is allowed to perform on the system Furthermore an inactivity timeout can b
187. tion happens to change the elements being used there is no need for the user to connect to the Vision Sensor using Intellect and reconfigure the Vision Tool A simple digital signal to the Vision Sensor can be used to indicate that a new element is ready to be learned In that case the system takes the element color code shape etc from the next image to be inspected and stores it as the new model 47 Intellect Software Now that the user is familiar with the system product and tool level parameters we will discuss how to access them This section explains the basics of the Intellect software After reading this section the user should be able to access all the parameters explained before and should be more comfortable with the system Intellect consists of two main parts One of them is the Intellect firmware which resides in the Vision Sensor The Intellect firmware is responsible for all the computations that happen inside Vision Sensors The user has direct control over the firmware by programing the user interface which translates everything for the firmware to execute The second part of Intellect is the software The Intellect software consists of the Intellect user interface and the Vision Sensor hardware emulator The user can only access the components that reside in the PC the Intellect user interface and the hardware emulator Using the Intellect user interface the user connects to a Vision Sensor and makes changes to the product o
188. trast to find features PatternCounting Count along a Line Vision Tool The Count along a Line Vision Tool in Pattern Counting mode is designed to detect and count features based on a learned pattern of grayscale pixels The mode can be very powerful at filtering out noise if the part features is consistent in it pixel intensity and pattern The Vision Tool uses normalized grayscale correlation to find the closed matched pattern along the line that matches the features trained pattern A pattern is a sequence of pixel intensities Since the Vision Tool learns the grayscale pixel intensity values no threshold is used for finding the pattern It is best used when detecting only edges or features does not provide for an adequate inspection and when the part has a signature of pixel values Pixel Counting Vision Tools Intensity and Color Counting The Pixel Counting Vision Tool calculates the amount of pixels within a threshold range or of a given color within a given region of the image The major purpose of this Vision Tool is to determine the presence or absence of image features by looking at an area The Vision Tool analyzes the pixels and determines how many of them are between an upper and lower threshold value for grayscale system or how many of them match the learned colors for a color system Figure 29 shows an example of its use 59 Figure 29 Use of a Pixel Counting Vision Tool to verify the presence and correct position of a label
189. understand the concepts and issues explained here 91 Dealing with Colors The main uses of the Pixel Counting Color Vision Tool Color Vision Tool are to detect defects and to verify that correct parts are used in an application Defect detection can be performed by learning the good colors of a part and detecting any color not in the good colors list in subsequent parts If the type of defect is known the bad colors can be learned instead and the images can be analyzed by checking for the presence of those colors only Part presence can be detected by learning the colors of a number of parts and verifying that the correct part is being used by inspecting subsequent images and comparing the colors present to the desired color Another way in which colors are used is to export them to other Vision Tools When that is done and another Vision Tool references the color areas of the imported color become light areas referred to as above threshold for grayscale systems and areas of other colors become dark areas referred to as below threshold for grayscale systems There are two ways to learn colors using the Pixel Counting Vision Tool single color learning and multi color learning The process for single color learning is illustrated in Figure 56 No Relearn Color gt Learn Color lt Is Learned Change Vision No Color Correct gt Tool Parameters o Parameters eed to L
190. unts of noise may be present However it is a computationally intensive Vision Tool which should only be used when other Vision Tools do not provide an adequate inspection NOTE Although this Vision Tool can be attached to a positioning Vision Tool to inspect the correct location it can only translate That is the Vision Tool will not inspect the part correctly if it is rotated Positioning Vision Tools This group of Vision Tools helps to locate parts and features when working with applications that need to account for part movement These Vision Tools are e Position along a Line o Line Mode Translation These Vision Tools look for edges or patterns along a certain path or in an area and then provide offsets in the horizontal and or vertical direction that would serve as position reference for other Vision Tools o Arc Mode Rotation these Vision Tools look for an edge or pattern along circular or elliptical paths They would provide angle information that can be used as position reference for other Vision Tools e Area Positioning o Blob Locating Finds the location of a part or area of a part based on blob parameters 64 o Object Locating Finds the location of a part or area of a part based on the edges o f the parts use geometric edge location o Pattern Locating Finds the location of a part or area of a part base on the intensity pattern representing the part using normalized grayscale correlation e line Fit Spec
191. used this chapter illustrates the use of their parameters and the functionality they add to the system Once the user becomes familiar with the internal structure of DVT Vision Sensors the use of these will become a very simple procedure because Intellect is designed to be an easy to use interface The DVT Vision Sensor hardware emulator is also explained in this chapter The hardware emulator is a very powerful tool that simplifies troubleshooting shortens setup and assists in training 27 As mentioned before Vision Sensors can take an image and analyze it to determine whether based on user defined parameters that is a good image or not Based on this output from the Vision Sensor the user can take the necessary action e g reject a part fix the production process etc The purpose of this section is to discuss the functionality inside the Vision Sensor Figure 8 shows the hierarchical tree determined by inner components of Vision Sensors DVT Vision System Level Sensor Inspection Inspection Product 1 Product 2 I BOUE LEVEI Vision Tool 1 Vision Tool 1 Tool Level Vision Tool 2 Vision Tool 3 Vision Tool 2 Figure 8 Hierarchical organization within the Vision Sensor At the top level we find the system parameters These parameters are common to every inspection that the Vision Sensor performs they affect the overall behavior of the Vision Sensor rather than that of a certain inspection Next at the product
192. ution of colors in the part Using this Vision Tool a multicolor model can be used For very similar colors which are difficult to differentiate with regular color Sensors the DVT Spectral Sensor should be used in combination with the Spectrograph Vision Tool Basically for gross differences the Pixel Counting Vision Tool should be used For parts that offer very little color difference and when the Pixel Counting Vision Tool does not offer the reliability needed a Color Monitoring Vision Tool should be used This Vision Tool requires that the area to be analyzed be of a uniform color no color variations are allowed In cases where the color difference is visually hard to detect the DVT Spectral Sensor should be used to compare the entire spectrum of the parts and make a more reliable decision The use of the DVT Spectral Sensor requires that the part to be analyzed be consistently placed because the positioning Vision Tools cannot not used by the DVT Spectral Sensor Part I dentification Identifying a part is a very broad type of application that generally entails defining differences between the parts and identifying those using Vision Tools There are several different techniques for achieving part identification and they depend mostly on the part being inspected The Identification Vision Tool Group contains Vision Tools that can learn multiple models using either color properties of the parts or 98 blob properties Other Vision Tools that
193. w Detection Vision Tool Category provides Vision Tools which find subtle flaws in parts DVT Script Tool DVT Script uses a DVT scripting language to expand the capabilities of the Image Inspection System Application Specific Vision Tools The Application Specific Vision Tools are customized for very specific inspection tasks 56 Counting Vision Tools for Presence Absence The Counting Vision Tools are generally used to simple Presence Absence applications and counting applications These Vision Tools perform basic checks for detection of features and edges or analyze the intensity level of the pixels in a certain area or linear path These Vision Tools are e Count along Line Vision Tool o Edge Counting These Vision Tools look for and count transitions from bright pixels to dark pixels and vice versa o Feature Counting These Vision Tools are an enhanced version of the EdgeCount Vision Tools besides detecting intensity transitions they also report the size of the regions between such transitions o Pattern Counting This Vision Tool learns a pattern and counts the number of instances of that pattern in the image e Count in Area Vision Tool o Blobs This Vision Tool counts the number of blobs found in an image based on user specified blob parameters o DObject Locate This Vision Tool finds the number of instances of a part or feature based on the learn region and user specified parameters o Pattern Match This Vision Too
194. whereas dimmer ones require longer exposure time There may be instances in which you must reduce your exposure time You have the following options to help reduce exposure time and still maintain overall image intensity e Increase the light aimed at the inspection area e Increase the gain on the CCD Gain is the ratio of output over input or in this case the overall increase in image brightness Increasing the gain makes the CCD more sensitive to light Caution high gain settings may produce a grainy image which may affect sensitive inspections e Use a lens with an adjustable aperture Many C and CS mount lenses have aperture controls Notes An aperture is the hole that lets light through the lens onto the imaging surface The larger the hole the more light can strike the CCD Opening the aperture may reduce the depth of field Doing so will make it more difficult to focus on objects if they vary in distance from the lens Increasing the exposure time slows down image acquisition process and will increase image blur for moving inspections Digitizing Time This parameter determines the precision of the analog to digital conversions in the image acquisition device The slower digitizing time allows for more precise conversions It is recommended to use the default value Visible changes in the image are not likely to be observed when changing this option Depending on the system users can choose between different digitizing tim
195. work Neighborh Grd rd Emulators e DIAGNOSTICS Unkno 169 254 1 255 255 0 0 00 90 68 00 Vision S DVT 545 Diagnostics 1 07 DVT 545 Favorites DVT Vision Sensor Unknown 10 22 50 225 255 255 0 0 5 Vision Se Intellect Version 1 3 0 DEBUG DVT 515 E Ethernet Adapters DVT vision Sensor 10 22 50 190 255 255 0 0 Vision Se Intellect Version 1 3 0 DEBUG DVT 515 DVT vision Sensor 10 22 50 225 255 255 0 0 00 90 68 00 7c Vision Se Intellect Version 1 3 0 DEBUG DVT 545 SmartImage Sensor 10 22 50 27 255 255 0 0 00 90 68 00 0c cf Vision Se FrarmeWork Version 2 6 4 Build Model 630 SmartImage Sensor 10 22 50 45 255 255 0 0 00 90 68 00 7c 00122 Vision Se FrameWhork Version 2 7 6 Build DVT 540 E Gregs 550 Unknown 10 22 50 49 255 255 0 0 00 90 68 00 f8 5502017 Vision Se Intellect Version 1 2 2 Build 01 DVT 550 I DWT Smart Camera Unknown 10 22 50 188 255 255 0 0 00 90 68 01 6e 53000001 Vision Se Intellect Version 1 2 0 Build 13 DVT 530 DIAGNOSTICS Unknown 10 22 50 160 255 255 0 0 00 90 68 00 00 53001222 Vision Se DVT 530 Diagnostics 1 4 0 Bui DVT 530 DVT Smart Camera 10 22 50 160 255 255 0 0 00 90 68 00 00 53001222 Vision Se Intellect Version 1 3 0 ALPHA DVT 530 E Ed_Tests30 10 22 173 224 255 255 0 0 00 90 68 00 ba 53002162 Vision Se Intellect Version 1 2 2 Build 01 DVT 530 DVT Smart Camera 10 22 50 25 255 255 0 0 00 90 68 00 f2 510121429 Vision Se

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