An Adaptive Pattern Recognition Methodology for Damage Classification in Composite Laminates

Composites present additional challenges for inspection due to their anisotropy, the conductivity of the fibers, the insulating properties of the matrix, and the fact that damage often occurs beneath the visible surface. This paper addresses the characterization of damage within composite materials, specifically for structural health monitoring (SHM). The presented research utilized Lamb wave testing coupled with pattern recognition methods, with the goal of providing the presence, type, and severity of damage with a high degree of confidence. An adaptive methodology is also presented to accommodate changes in structural response that are not attributable to damage, such as ageing, maintenance and repair. The results have shown that PR methods can be used to successfully characterize damage in composites, with results that would improve further with additional training data