Delamination Defect Identification in CFRP Laminates using Improved Elliptical Localization and Lamb Wave Probabilistic Imaging

Carbon fiber-reinforced polymer (CFRP) is widely used in aerospace and other industrial fields due to its high strength-to-weight ratio, excellent temperature and corrosion resistance. However, manufacturing-induced delamination defects can seriously compromise structural integrity, making nondestructive evaluation (NDE) essential. This paper proposes an improved defect identification method that combines an enhanced elliptical localization algorithm with Lamb wave-based probabilistic imaging for promising delamination identification in CFRP laminates under the tested conditions. First, the dispersion curves of Lamb waves are calculated using the 1D-GLL-SAFE method in SAFEDC software, and S0/A0 modal wave velocity radar maps are generated to visualize directional dependence in the anisotropic structure. Finite element models with controlled delamination defects are then established in ABAQUS to simulate Lamb wave propagation and defect interaction. Simulation results show absolute localization errors of 3.91 mm and 3.61 mm, with relative errors of 1.85% and 2.55%. An experimental setup incorporating ultrasonic excitation and fiber Bragg grating (FBG) sensing is developed to test CFRP specimens with pre-embedded defects. Experimental results demonstrate the method’s accuracy, with absolute errors of 2.84 mm and 3.82 mm, corresponding to relative errors of 1.34% and 2.71%. This study provides a validated, integrated solution for high-precision nondestructive testing (NDT) and localization of delamination defects in CFRP structures through simulations and experiments.