Multi-site damage localization in anisotropic plate-like structures using an active guided wave structural health monitoring system

A new approach for structural health monitoring using guided waves in plate-like structures has been developed. In contrast to previous approaches, which mainly focused on isotropic or quasi-isotropic plates, the proposed algorithm does not assume any simplifications regarding anisotropic wave propagation. Thus, it can be used to improve the probability of detection. In this paper the mathematical background for damage localization in anisotropic plates will be introduced. This is an extension of the widely known ellipse method. The formalism is based on a distributed sensor network, where each piezoelectric sensor acts in turn as an actuator. The automatic extraction of the onset time of the first waveform in the differential signal in combination with a statistical post-processing via a two-dimensional probability density function and the application of the expectation-maximization algorithm allows a completely automatic localization procedure. Thus, multiple damages can be identified at the same time. The present study uses ultrasonic signals provided by the spectral element method. This simulation approach shows good agreement with experimental measurements. A local linear neural network is used to model the nonlinear dispersion curves. The benefit of using a neural network approach is to increase the angular resolution that results from the sparse sensor network. Furthermore, it can be used to shorten the computational time for the damage localization procedure.