automated weld integrity analysis using 3d point data

AUTOMATED WELD INTEGRITY ANALYSIS USING 3D POINT DATA

Matt Swanson, Eric Johnson, Alexander StoytchevIowa 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

Results of Bad Welds

Some Weld Types

This Work Focuses on T-fillet Welds

Bad vs Good Welds

Previous Approach

Previous Approach

Previous Approach

Previous Approach

Dental Molding is applied Molding is cross sectioned

Previous Approach

Previous Approach

Previous Approach

R

Theta

Previous Approach The bending and the membrane

stress concentration factors of the weld are given by:

469.572. )(512.1 rtK b

t

469.37. )(388.1 rtK m

t

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 vu = q - p v = r - p K-means cluster on the plane

created fromthe cross product of u and v Fit Planes to Plate

Clusterscalculate plane from histogram of

green andblue clusters

Our Approach (3) Extract Weld Parameters

Slice Weld ClusterSlice 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(Compare the two

Approaches)

Results (Slice #7 on Weld #1)

Results (Weld #1)

Results (Weld #1)

2.2% difference

Results (Weld #2)

1.9% difference

Video

ART Tracker

ART Tracker

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

Summary and Conclusions

Questions?