Application of Neural Networks for Classification of Eddy Current NDT Data

  • L. Udpa
  • S. S. Udpa
Part of the Review of Progress in Quantitative Nondestructive Evaluation book series


The inverse problem in nondestructiye evaluation involves the characterization of flaw parameters given a transducer response signal. In general the governing equations and boundary conditions describing the underlying physical phenomena are complex. Consequently analytical closed form solutions can be obtained only under. strong simplifying assumptions with regard to geometry and linearity of the problem. This precludes their use as direct inverse models for solving realistic NDT problems necessitating the need for using indirect inverse models based on pattern recognition algorithms. These inverse models classify the NDT signal as belonging to one of the classes of defects stored in a data bank as shown in Fig. 1.


Output Node Inverse Model Fourier Descriptor Pattern Recognition Algorithm Analytical Closed Form Solution 
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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Copyright information

© Springer Science+Business Media New York 1990

Authors and Affiliations

  • L. Udpa
    • 1
  • S. S. Udpa
    • 1
  1. 1.Department of Electrical EngineeringColorado State UniversityFort CollinsUSA

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