Classification of Ultrasonic NDE Signals using the LMS Algorithm and SAFT based Imaging

D. Kim (Korea)


Classification, Ultrasonic NDE, SAFT, LMS


Ultrasonic inspection methods are widely used for detect ing flaws in materials. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classi fication of the signals in the feature space. This paper describes an approach which uses LMS method to deter mine the coordinates of the ultrasonic probe followed by the use of SAFT to estimate the location of the ultrasonic reflector.

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