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Effects of Microstructure and Bond Quality on the Ultrasonic Evaluation of Dissimilar Metal Friction Welds

  • Graham H. Thomas
  • Jay R. Spingarn
Chapter
Part of the Review of Progress in Quantitative Nondestructive Evaluation book series

Abstract

During the last several years we have been investigating ultrasonic techniques for evaluating the quality of solid state weld interfaces [1,2]. Promising results have been obtained on a variety of different solid state welds by extracting features from the ultrasonic waveforms and applying pattern recognition algorithms to separate acceptable from unacceptable welds. In general, the primary difficulty in evaluating solid state interfaces is separating the influence of microstructural variations (volumetric) from the effects of interface defects (planar). To better understand the influence of microstructure on our assessment of solid state welds, we have ultrasonically and destructively analyzed steel-to-aluminum friction welds of varying weld quality and microstructure. A matrix of samples was prepared to produce microstructural variations in the aluminum. Since the steel’s microstructure was unaffected by our friction weld process, acoustic energy sent from the steel side was primarily influenced by the bondline. Thus, we could monitor the influence of the microstructure and bond quality from the aluminum side and the bondline alone from the steel side. First, ultrasonic data from the steel side of our friction welds were processed with feature extraction and pattern recognition techniques as in our previous studies to determine solid state bond quality. Then data from the aluminum side were processed the same way and the classification results were compared to the results obtained from the steel side. The discrepancies in the classification results were caused the microstructure variation in the aluminum.

Keywords

Weld Quality Friction Welding Ultrasonic Signal Microstructural Variation Pattern Recognition Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Thomas, G. H., and Spingarn, J. R., “Ultrasonic Evaluation and Imaging of Tube Closure Welds,” Proc. Review of Progress in Quantitative Nondestructive Evaluation, Vol. 6B, edited by D. O. Thompson and D. E. Chimenti, 1986.Google Scholar
  2. 2.
    Thomas, G. H., and Spingarn, J. R., “Ultrasonic Nondestructive Evaluation of Solid State Welds,” Proc. Review of Progress in Quantitative Nondestructive Evaluation, Vol. 7B, edited by D. O. Thompson and D. E. Chimenti, 1987.Google Scholar
  3. 3.
    Armstrong, B. L. et al, “Ultrasonic Analysis of Inertia Welds,” Proc. Review of Progress in Quantitative Nondestructive Evaluation, Vol. 5B, edited by D. O. Thompson and D. E. Chimenti, 1985.Google Scholar
  4. 4.
    Duda and Hart, Pattern Classification and Scene Analysis. John Wiley and Sons, New York, 1973.Google Scholar

Copyright information

© Springer Science+Business Media New York 1990

Authors and Affiliations

  • Graham H. Thomas
    • 1
  • Jay R. Spingarn
    • 1
  1. 1.Sandia National LaboratoriesLivermoreUSA

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