Estimation and Application of 2-D Scattering Matrices for Sparse Array Imaging of Simulated Damage in Composite Panels

Reliable detection of damage in composites is critically important for failure prevention in the aerospace industry since these materials are more frequently being used in high stress applications. Structural health monitoring (SLIM) via guided wave sensors mounted on or embedded within a composite structure can help detect and localize damage in real-time while potentially reducing overall maintenance costs. One approach to guided wave SLIM is sparse array imaging via the minimum variance algorithm, and it has been shown in prior work that incorporating expected scattering from defects of interest can improve the quality of damage localization and characterization. For this study, simulated damage in the form of attached magnets was used for estimating scattering from recorded wavefield data. Data were recorded on a circle centered at the damage location from multiple incident directions before and after the magnets were attached. Baseline subtraction is used to estimate scattering patterns for each incident direction, and these patterns are combined and interpolated to form a full 2-D scattering matrix. This matrix is then incorporated into the minimum variance imaging algorithm, and the efficacy of this scattering estimation methodology is evaluated by comparing the resulting sparse array images to those generated using simpler scattering assumptions.