Probabilistic damage diagnosis of composite laminates using Bayesian inference

In this paper, a non-deterministic delamination location and size detection framework is proposed. The delamination probability image using Lamb wave-based damage detection is constructed using the Bayesian updating technique. First, the algorithm for the probabilistic delamination and size location detection framework using Bayesian updating (Bayesian Imaging Method - BIM) is developed. Following this, a composite coupon fatigue testing setup is given and the corresponding lamb wave diagnosis signal is collected and interpreted. Next, the obtained signal features are incorporated in the Bayesian Imaging Method for the delamination size and location, as well as their confidence bounds, detection. The damage detection results using the proposed methodology are compared with X-ray images for verification and validation. Finally, some conclusions and future works are drawn based on the proposed study.