Classification of Acoustic Emission Signal Sources Using Genetic Programming

Abstract

Genetic Programming (GP) is used to classify the Acoustic Emission (AE) signal to different source of signals. GP has the ability to discover the relationship among the observed data and express them mathematically. GP based technique has an advantage over conventional statistical technique like maximum likelihood estimate, nearest neighbor classifier and etc, because they are distribution free i.e. no a priori knowledge is required about the distribution of data. The data is obtained through an AE test using pulse, pencil and spark signal source on the surface of solid steel block. The signal parameters are measured using AET 5000 system, A set of expert system like rules is extracted from the GP. These rules are used directly to classify the AE signals. Classification of AE signal using genetic programming is found to be effective.