Lamb wave signals for damage detection using a probability-based imaging algorithm

Identification of multiple notches in an aluminium plate was investigated with the aid of probability-based imaging evaluation of Lamb wave signals activated and captured by a piezoelectric sensor network. A signal processing algorithm featuring signal synchronization and correlation is proposed to facilitate the extraction of damage-scattered waves, by the means of which the corresponding arrival times of the scattered waves are obtained. Using a virtually-meshed grid in the plate, an image with respect to the probability of the arrival time at individual nodes is achieved, indicating the location of damage as perceived by individual actuator-sensor paths. Compromised and conjunctive data fusion techniques are applied to aggregate the images for all engaged actuator-sensor paths, to provide a complete appraisal of the location of damage. The diagnostic results demonstrate that the proposed approach is capable of identifying multiple notches with good accuracy in terms of their position.