Lamb Wave-based Depth Characterization of Acoustic Emission Sources in Complex Metallic Plate-like Structures

Abstract

This paper demonstrates an inversion algorithm for characterizing the depth of acoustic emission (AE) sources in complex metallic plate-like structures. The characterization is motivated by gaining insight into early-stage fatigue crack propagation in such structures. The primary inputs to the algorithm are narrowband-filtered AE signals from a network of sensors and an estimate of the planar source location. The layout of the sensor network is specially designed to make use of locally isotropic regions in a complex structure. The algorithm is based on automatically extracting the depth-dependent amplitude ratio between the fundamental Lamb modes contained in the AE signals. A finite element model is designed to solve the forward problem of Lamb wave motion due to a given source, from which the relation between source depth and amplitude ratio is determined. The proposed algorithm was evaluated on a 1 m × 1 m section of a 2025-T6 aluminum civilian aircraft fuselage. Validation of the algorithm was achieved by generating controlled AE sources (Hsu-Nielsen pencil lead breaks) at various depths along the edges of the fuselage panel. Good agreement was found in the between the true and estimated source depths. The experiments demonstrate the ability to distinguish between sources originating near the mid-plane of a plate-like structure from those near the surface. Moreover, it is demonstrated that the fast computation of the inversion algorithm has great potential for real-time monitoring applications.