Classification of Ultrasonic Signals

In ultrasonic defectoscopy it is very difficult to detect flaw in materials with coarse-grain structure. The ultrasonic signals measured on these materials contain echoes which are very similar to fault echo. These echoes arise from grains which are contained in material. For detection of flaw various methods for suppressing of echoes from grains have to be used. In this work we used the method for filtering of ultrasonic signal based on discrete wavelet transform. For classification of ultrasonic signals in A-scan we used pattern recognition method called support vector machines. In this study we classify signals with fault echo, echo from weld and back-wall echo. Ultrasonic signals were measured on material used for constructing airplane engines. The experimental results indicate the performance of the proposed approach.