Ultrasonic inspection methods are commonly used in the nondestructive evaluation of welds to detect flaws in the weld region. An important characteristic of ultrasonic inspection is the ability to identify the type of discontinuity that gives rise to a particular signal. Standard techniques rely on differences in individual A-scans to classify the signals. This paper proposes an ultrasonic signal classification technique based on the information in a group of signals. The approach is based on a 2-dimensional transform and principal component analysis, for generating a reduced dimensional feature vector for classification. Results of applying the technique to data obtained from the inspection of welds are presented.
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