Active-Sensing Lamb Wave Propagations for Damage Identification in Honeycomb Aluminum Panels

This paper presents a novel approach for Lamb wave based structural health monitoring(SHM) in honeycomb aluminum panels. In this study, a suite of three signal processing algorithms are employed to improve the damage detection capability. The signal processing algorithms used include wavelet attenuation, correlation coefficients of power density spectra, and triangulation of reflected waves. Piezoelectric transducers are utilized as both sensors and actuators for Lamb wave propagation. These SHM algorithms are built into a MatLab interface that integrates and automates the hardware and software operations and displays the results for each algorithm to the analyst for side by side comparison. The effectiveness of each of these signal processing algorithms for SHM in honeycomb aluminum panels under a variety of damage conditions is then demonstrated.