An algorithm for multi-damage size estimation of composite laminates

Abstract

Localization and size estimation of composite damage are challenging but essential for composite performance evaluation. This paper proposes a new methodology for the size estimation of multi-damage in composite laminates using Lamb wave technology. The pure A0 modal of Lamb wave is excited to avoid dispersion and multi-modal effects of Lamb wave. An extraction algorithm is introduced to obtain the first wave packet and time-of-flight. According to the results obtained by the extraction algorithm, the Bayesian-hybrid localization algorithm based on the reconstruction algorithm for probabilistic inspection of damage and modified delay-and-sum (MDAS) is performed to localize damages. The damage boundaries are obtained through convex enveloping a series of damage boundary points identified by MDAS. An adaptive Gaussian mixture model based on Akaike’s Information Criterion and Bayesian Information Criterion is designed to remove abnormal boundary points. The proposed method is numerically investigated and validated through multi-damage experiments. The results demonstrate that it can accurately estimate the locations and boundaries of multi-damage in composite laminates.