Delamination detection in composite laminates using Lamb wave tomographic method based on sparse and probabilistic reconstruction

Composite materials are widely employed in many industrial fields, and transmitted Lamb wave-based methods, represented by tomography, have been widely utilized for delamination detection in composite laminates. Nevertheless, conventional Lamb wave tomography may suffer from large artifacts and other problems. To break these limitations, a Lamb wave tomographic method based on sparse and probabilistic reconstruction for delamination detection in composite laminates is proposed in this study. Firstly, Lamb wave propagation in delaminated laminates is analyzed, from which it can be derived that delamination can cause the time-of-flight (ToF) delay of A0 mode. Then, differences in ToF between intact and delaminated laminates are calculated and constitute the time difference vector, which can be represented by the product of the length matrix and the slowness difference vector. Since the delamination distribution is sparse, the slowness difference vector satisfies the sparse assumption, which indicates that it can be solved with sparse reconstruction techniques. Furthermore, to improve the quality of sparse reconstruction, the probability distribution is introduced as a prior weight during the solving procedure. Finally, numerical and experimental investigations are implemented. The imaging results can provide a more precise estimation of delamination size and location, which demonstrates the performance improvement of the presented approach.