ENTROPY APPROACH FOR FILTERING ACOUSTIC EMISSION SIGNALS

Abstract

The acoustic emission (AE) method has been successfully used in recent years to monitor the condition of industrial and civil infrastructure structures. In AE, time-of-arrival (ToA) estimation is considered a key parameter for the accurate location of a growing defect. This paper describes an entropy-based filtering approach to improve the ToA estimation of a signal in a noisy environment compared to the commonly used Akaike Information Criterion (AIC). The proposed method consists of coarsening the input data using the Crutchfield-Packard algorithm and calculating the local (instantaneous) entropy. In the present study, it is demonstrated that the local entropy of the noise component of the signal the local entropy of the useful (informative) part can be distinguished. As a result, the approach allows filtering out the noise component by selecting appropriate filtering parameters. The proposed approach has been tested on experimental data obtained on an aluminium plate used to pinpoint an AE source. The entropic approach demonstrates higher accuracy in final target location of AE sources at significant noise levels compared to classical AIC.