Application of Neural Networks for Classification of Eddy Current NDT Data

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1990
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Udpa, L.
Udpa, S.
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Review of Progress in Quantitative Nondestructive Evaluation
Center for Nondestructive Evaluation

Begun in 1973, the Review of Progress in Quantitative Nondestructive Evaluation (QNDE) is the premier international NDE meeting designed to provide an interface between research and early engineering through the presentation of current ideas and results focused on facilitating a rapid transfer to engineering development.

This site provides free, public access to papers presented at the annual QNDE conference between 1983 and 1999, and abstracts for papers presented at the conference since 2001.

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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.

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Mon Jan 01 00:00:00 UTC 1990