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Automated Weld Integrity Analysis Using 3D Point Data for Improved Quality Assurance

This research presents an innovative method for automated weld integrity analysis using high-resolution 3D point data. Bad welds incur high costs due to warranty claims and downtime, while traditional quality assurance methods are time-consuming. Our approach involves scanning the weld with an Aramis camera, generating high-resolution point clouds, and using advanced algorithms to extract weld parameters. Results demonstrate a significant reduction in measurement time and increased accuracy in assessing weld quality, paving the way for future handheld scanning devices and integration into manufacturing processes.

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Automated Weld Integrity Analysis Using 3D Point Data for Improved Quality Assurance

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  1. AUTOMATED WELD INTEGRITY ANALYSIS USING 3D POINT DATA Matt Swanson, Eric Johnson, Alexander Stoytchev Iowa State University John Deere

  2. Motivation • Bad welds are expensive • Warranty claims • Down time • Current quality assurance methods are time consuming • Hand measuring weld parameters • Procedure can take 1-2 hours for a single weld

  3. Results of Bad Welds

  4. Some Weld Types

  5. This Work Focuses on T-fillet Welds

  6. Bad vs Good Welds

  7. Previous Approach

  8. Previous Approach

  9. Previous Approach

  10. Previous Approach Dental Molding is applied Molding is cross sectioned

  11. Previous Approach

  12. Previous Approach

  13. Previous Approach R Theta

  14. Previous Approach The bending and the membrane stress concentration factors of the weld are given by:

  15. Our Approach (1) Scan the Weld • Powder weld with reflective material • Aramis Camera • Extract high resolution 3D point clouds • 50 micron resolution

  16. Our Approach (2) Determine Geometry Cluster Normals For every 3 neighboring points (p,q,r) calculate vectors u and v u = q - p v = r - p K-means cluster on the plane created from the cross product of u and v Fit Planes to Plate Clusters calculate plane from histogram of green and blue clusters

  17. Our Approach (3) Extract Weld Parameters • Slice Weld Cluster Slice weld along contour of the interesection between the weld and plane • Fit Circle to Weld Toe • Fit R1 and R2 • Extract interior points • Circle fit

  18. Results(Compare the two Approaches)

  19. Results (Slice #7 on Weld #1)

  20. Results (Weld #1)

  21. Results (Weld #1) 2.2% difference

  22. Results (Weld #2) 1.9% difference

  23. Video

  24. ART Tracker

  25. ART Tracker

  26. Future Work • Build a handheld device to scan welds • Couple a pico-projector with a web cam • Extend our software to scan entire assemblies and identify the welds on them automatically • Test under factory conditions

  27. Summary and Conclusions

  28. Questions?

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