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Vision-Based Metrology

Vision-Based Metrology. IET 405 Vision Based Metrology Project. Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar. Vision-Based Metrology History. Vision-Based Metrology refers to the technology using optical sensors and digital image processing hardware and software to:

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Vision-Based Metrology

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  1. Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

  2. Vision-Based Metrology History • Vision-Based Metrology refers to the technology using optical sensors and digital image processing hardware and software to: • Identify • Guide • Inspect • Measure objects

  3. Vision-Based Metrology History • Vision-Based Metrology inspection systems evolved from the combination of microscopes, cameras and optical comparators

  4. Vision-Based Metrology History • Vision-Based Metrology is extensively used in general industrial applications such as the manufacturing of: • Electronics • Automotive • Aerospace • Pharmaceutical • Consumer products • Vision-Based Metrology is being utilized in the automatic identification and data collection market as a complementary or alternative technology to traditional laser scanning devices for reading bar codes

  5. Vision-Based Metrology History • Early systems were integrated into packaging lines for optical character recognition and proved to be a reliable way to check the accuracy of product codes and label information. • Today, high-resolution cameras, advances in software and imaging processors, and the availability of powerful, inexpensive compact computers have made vision systems faster and more reliable than ever.

  6. When does a company need a vision system? • Some products require 100-percent product inspection with documented inspection results. • In other cases a vision system may be needed for high production product inspection • Vision systems provide a means of increasing yield-that is, the ratio of good parts to bad parts. • When a serial defect is spotted, the system not only recognizes it but can stop the conveyor and inform the operator of the defect and its magnitude. • The yield factor is particularly important in manufacturing industries that produce large volumes, as in the compact disc and pharmaceutical industries.

  7. Vision-Based Metrology inAutomobile Wrecks • Vision Based Metrology is now being used to focus on the movement of objects along with their deformation • This is being used in many car wreck investigations

  8. Vision-Based Metrology in Automobile Wrecks • Two consecutive images were grabbed from a high speed video sequence • A displacement field of a car at a certain moment is presented

  9. Vision-Based Metrology in Automobile Wrecks • The deformation pattern was obtained from the principle vector analysis. • This analysis allows the representation of the deformation pattern.

  10. Vision-Based Metrology in Weather Patterns • Vision-Based Metrology has also been used to study weather patterns • Flow information from a tornado is able to be extracted for scientists to attempt to learn more about them

  11. Vision-Based Metrology in Companies • There are many companies that use vision inspected systems today • Some of the bigger ones are ICS/INEX and PPT Vision

  12. ICS/INEX • INEX can be traced all the way back to the early 1900’s when they developed a system called OPTI-Tron which inspected bottle beverages • The OPTI-Tron system would eventually become the OPTISCAN bottle inspector; a worldwide standard in container inspection with thousands of units installed. • The introduction of the company's SuperInspector 1055 became the first commercial machine inspection system to integrate camera and computer technologies

  13. PPT Vision • Founded in 1982, PPT specializes in industrial applications where accuracy, repeatability, high speed and flexibility are important requirements. • They are the world leader in the design and manufacture of completely digital 2D machine vision systems. • PPT's 2D machine vision product line is sold on a global basis to end-users, system integrators, and OEM's • PPT is involved primarily in: • Electronics • Semiconductor components • Automotive • Medical devices • Pharmaceutical and packaged goods

  14. Quality Inspection at Work Polymer Membrane: Note texture defects Machined Aluminum Bar: Note tool-chatter marks Stamped Metal Package: Note scratch on grinded surface

  15. Vision System Pictures Missing Fuse

  16. Golf Ball Specifications • Weight: Less than or equal to 1.620 Ounces • Size: Greater than or equal to 1.680 Inches • Shape: Must be symmetrical

  17. USGA Golf Ball Testing • A ball passes USGA size inspection if it falls, under its own weight, through a 1.680 inch diameter ring gauge fewer than 25/100 times in randomly selected positions. • Temperature is constant at 23° C (73.4 ° F). • Humidity is held constant.

  18. Test Outline • Random sample testing for different brands of golf balls • Determine diameter • Analyze the results

  19. Procedure • Place the ball on the test stand • Take a picture from a standard height for each golf ball being tested • Analyze the image using National Instruments® vision analysis software • Compare the image to the standard size for the USGA ball specification • Compile and analyze the data from the testing • Present information in graphical form

  20. Test Device • Designed using Solidworks® CAD program • Made of extruded aluminum • Center positioned ball holder that provides consistent images for each ball tested • Camera is secured using the tripod mount

  21. Final Drawing

  22. Test Device

  23. Images from National Instruments® IMAQ Vision Builder

  24. Images from the Vision Software Horizontal and Vertical Clamp Horizontal Clamp

  25. Measurement Data • Able to see variance between different golf balls • Tolerance we detected was about 1.680 ± .010 inches • The device performed as expected to allow us to complete the vision analysis

  26. Conclusion • Vision systems are a reliable way to accurately measure items • A vision system can measure minute details to a precise and accurate level • We were able to observe this with golf balls varying just a few pixels • We now have a better understanding of vision systems and how they work

  27. References http://www.cranfield.ac.uk/sme/amac/research/metrology/tornado.htmhttp://www.cranfield.ac.uk/sme/amac/research/metrology/carcrush.htmhttp://www.qualitydigest.com/mar98/html/vision.htmlhttp://www.rvsi.com/Pages/about.htmhttp://www.inexvision.comhttp://www.pptvision.comhttp://www.visionxinc.com

  28. Acknowledgements Alufab® located in Mt. Carmel, Ohio Donated materials for the prototype Donated their shop and tools for the construction Special thanks to Dr. Allameh for allowing us to use his software and office for this project

  29. Questions?

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