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AUTOMATED WELD INTEGRITY ANALYSIS USING 3D POINT DATA. Matt Swanson, Eric Johnson, Alexander Stoytchev Iowa State University John Deere. Motivation. Bad welds are expensive Warranty claims Down time Current quality assurance methods are time consuming Hand measuring weld parameters
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AUTOMATED WELD INTEGRITY ANALYSIS USING 3D POINT DATA Matt Swanson, Eric Johnson, Alexander Stoytchev Iowa State University John Deere
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
Previous Approach Dental Molding is applied Molding is cross sectioned
Previous Approach R Theta
Previous Approach The bending and the membrane stress concentration factors of the weld are given by:
Our Approach (1) Scan the Weld • Powder weld with reflective material • Aramis Camera • Extract high resolution 3D point clouds • 50 micron resolution
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
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
Results (Weld #1) 2.2% difference
Results (Weld #2) 1.9% difference
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