Nonlinear guided wave damage imaging in composite structures using a sparse sensor network

Composite materials are increasingly being used in automotive, aerospace and other modern industrial sectors because of their high specific stiffness and strength. Yet, composites are quite susceptible to damages and defects which can be introduced during the manufacturing and/or its operational life. One possibility to detect and localize damage is to inspect the composite structures with guided waves using a sparse sensor network. A damage map can be reconstructed by using a probabilistic guided wave imaging modality, e.g., the well-known Reconstruction Algorithm for the Probabilistic Inspection of Damage (RAPID). For some applications, however, the baseline-dependent nature of RAPID makes it ineffective due to uncertainty of environmental conditions (e.g. temperature and moisture) and/or the absence of reference signals on a healthy specimen. In this study, nonlinear wave/defect interactions are investigated in order to achieve a baseline-free guided wave imaging modality. As such, the conventional RAPID is extended to a nonlinear version, called NL-RAPID, which does not require any baseline data making it very robust to changes in the environmental condition. The performance of the proposed NL-RAPID is evaluated on a synthetic dataset generated by a finite element model as well as on an aircraft A320 stiffened composite panel. To understand the performance and robustness of the developed baseline-free NL-RAPID method for damage imaging, a parametric study on several key (experimental) factors is performed. The obtained results show the good performance of the proposed baseline-free NL-RAPID method for efficiently localizing defects in composite panels.

Publication year:2023

Accessibility:Open