A State-of-art on Damage Detection of Composite Structure Using Lamb Wave and Deep Learning Techniques

Composite materials have garnered the attention of high-tech companies due to their significant benefits, such as high stiffness, corrosion resistance, good wear resistance, and high mechanical strength. However, these materials often suffer from damage due to their heterogeneous nature, and the inability to identify and recognize flaws in the early stages can lead to catastrophic failures. By applying non-destructive testing and evaluation, flaws can be detected and characterized, potentially reducing unplanned breakdowns and repair costs. This review examines current findings on early interlaminar and intralaminar damage detection and localization using Lamb waves and recent deep learning techniques. Additionally, this work addresses existing research gaps and highlights potential opportunities for future research and improvements in the field of structural health monitoring.