Classification of ultrasonic signals

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