A semi-analytical multimodal Lamb wave imaging algorithm for damage identification in structural health monitoring

Rapid damage identification in structural health monitoring (SHM) is critical for ensuring structural integrity and safety. Although Lamb waves exhibit high sensitivity to damages, quantitative correlation between multimodal time-of-flight (TOF) differences and damage parameters remains insufficiently explored. In this paper, we proposed an efficient damage identification algorithm based on multimodal Lamb wave TOF differences. The core of the method is a semi-analytical inversion model that reveals the relationship between the multimodal TOF differences and damage parameters. It provides a rapid way to obtain the residual thickness and length of the damage. Moving a transmitter-receiver pair is used to scan the whole detection area. The damage was located at the intersection of abnormal pathways. Dynamic baseline calibrationthrough DBSCAN clustering eliminates historical reference dependency while distinguishing damage paths. Tests on aluminum specimens show the range of localization and thickness accuracy. Simulations and experiments confirm its efficacy for identifying corrosion-type damage, demonstrating significant potential for cost-effective SHM deployment in large-scale structures.