Ultrasonic NDE discrimination with the gradient descent algorithm and SAFT image processing

Ultrasonic inspection methods are widely used for detecting flaws in materials. One of the most popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature space. This paper describes an approach which uses LMS method to determine the coordinates of the ultrasonic probe followed by the use of SAFT to estimate the location of the ultrasonic reflector. The method is employed for discriminating NDE signals from the steam generator tubes in a nuclear power plant. The results obtained by using this scheme, of discriminating the ultrasonic signals from cracks and deposits within steam generator tubes, are presented.