An approach based on expectation-maximization algorithm for parameter estimation of Lamb wave signals

In the structural health monitoring or nondestructive examination system based on the Lamb wave technology, the accurate and valid characteristics of wave packet extracted from the signal are critical factors to evaluate damage. However, the dispersion effect and the multi-mode characteristic in the elastic wave make the data extraction difficult and degrade the resolution, and therefore further prevent the effectiveness of Lamb wave for damage detection. In this study, we proposed a model-based approach for extracting effective characteristics from the noisy signals. By taking the narrow band Gabor pulse as the incident pulse and considering the general non-linear frequency dispersion (quadratic dispersion), we developed a model with five parameters to model the dispersive wave packet and obtained the parameter vector of each wave packet by the expectation-maximization (EM) algorithm. The parameters in the model present the characteristics of signals, which can be further applied to locate and evaluate the structure's damage. To study the convergence property, synthetic signals with different sampling rates and noise intensities were considered. Furthermore the developed approach is also verified by the experimental data from an isotropic aluminum plate.