Objective Ultrasonic Characterization of Welding Defects Using Physically Based Pattern Recognition Techniques

  • S. F. Burch


Computer-based methods for analysing ultrasonic data to distinguish between different defect types have been based on a variety of techniques such as adaptive learning [1], artificial intelligence [2] and statistical pattern recognition [3]. The uncertain classification reliability of these techniques when applied to a range of realistic defect types has, however, often been a significant practical limitation to their use.


Defect Type Planar Defect Statistical Pattern Recognition Inspection Technique Defect Class 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    M. F. Whalen, L. J. O’Brien, and A. N. Mucciardi, Proceedings of the DARPA/AFML Review of Progress in Quantitaive NDE, AFWAL-TR-80-4078, 1980.Google Scholar
  2. 2.
    L. W. Schmerr, K. E. Christensen, and S. M. Nugen, in Review of Progress in Quantitative NDE, edited by D. O. Thompson and D. E. Chimenti (Plenum Press, New York, 1987), Vol. 6A, pp. 879–887.Google Scholar
  3. 3.
    J. L. Rose, J. Nestleroth, L. Niklas, O. Ganglbauer, J. Ausserwoeger, and F. Wallner, Materials Eval., 42, 433–438, 443 (1984).Google Scholar
  4. 4.
    S. F. Burch, and N. K. Bealing, NDT International, 19, 145–153 (1986).CrossRefGoogle Scholar
  5. 5.
    S. F. Burch, and N. K. Bealing, paper presented at 21st Annual British Conference on NDT, Newcastle, Sept. 1986.Google Scholar
  6. 6.
    B. J. Smith, Brit. J. NDT, 28, 9–16 (1986).Google Scholar
  7. 7.
    P. M. Gammell, Ultrasonics, 19, 73–76 (1981).CrossRefGoogle Scholar
  8. 8.
    G. P. Singh, and R. C. Manning, NDT International, 16, 325–329 (1983).CrossRefGoogle Scholar

Copyright information

© Plenum Press, New York 1988

Authors and Affiliations

  • S. F. Burch
    • 1
  1. 1.Materials Physics and Metallurgy DivisionHarwell LaboratoryOxfordshireUK

Personalised recommendations