Optimal Mother Wavelet Selection for Lamb Wave Analyses

Abstract

Structural health monitoring (SHM) system, usually consisting of a sensor network for collecting the structural response signal and data analysis algorithms for interpreting the signal, plays a significant role in fatigue life and damage accumulation prognostics. Wavelet transform (WT) has gained popularity as an efficient means of signal processing in SHM, in which an optimal mother wavelet-based WT can carry out feature extraction with high precision. This article is to provide criteria of optimal mother wavelet selection in Lamb wave analysis for SHM, motivation of which is that small error in Lamb wave analysis can result in much larger error in damage localization because of very fast propagating velocities of Lamb waves. A concept, Shannon entropy of wavelet coefficients, was established to calibrate the degree of optimization of the selected mother wavelet. As application, various mother wavelets selected using the proposed criteria were applied to Lamb wave signals acquired from CF/EP composite laminates containing delamination. With the optimum mother wavelet, the essential information of the delamination-generated Lamb waves was achieved with high precision. The results demonstrate the excellent capacity of the approach for selecting the most appropriate mother wavelets for Lamb wave analyses and therefore damage localization.