Lamb wave damage imaging method based on multimodal dispersion compensation and compressive sensing

To address the challenges of wave packet broadening and signal distortion caused by multimodality and dispersion effects in Lamb wave-based damage detection for carbon fibre-reinforced polymer (CFRP) laminates, this paper proposes an imaging method that combines multimodal dispersion compensation and compressive sensing (CS). First, the Rayleigh-Lamb equation is solved using the T300/5028 material parameters to establish the dispersion characteristic model. A baseline-free multimodal dispersion compensation technique is developed for performing frequency-domain phase correction and time-domain signal reconstruction, allowing accurate estimation of the compensation distance between each sensor and the damage. Subsequently, a CS-based imaging algorithm that fuses delay-and-sum (DAS) and sparse reconstruction is proposed and verified using finite‑element simulations and experimental tests. The results show maximum localisation errors of 2.03 ± 0.05 mm in simulations and 2.31 ± 0.56 mm in experiments. This work provides theoretical insights and experimental support for the high-precise identification of delamination damage in anisotropic composite materials.