A novel wave tomography method for defect reconstruction with various arrays

In order to reconstruct the possible defects on the plate surface with arrays, a new wave tomography method based on the method of moments is established in this paper. According to the relationship between the probe number and grid amount, two algorithms, that is, the neural network and principal component analysis (PCA), are proposed and used to solve the ill-conditioned inversion equations. The neural network makes imaging feasible even if input data are not enough, and the PCA can greatly improve the computational efficiency via reducing the matrix dimension. Both numerical simulations and experimental measurements are conducted with the algorithm's correctness and high precision validated. After investigating the influence of probe number on imaging quality, it is demonstrated that the algorithm can exactly predict the defect location when the input scattering data is not enough or fewer probes are arranged. More probes are needed for reconstructing the specific shape and thickness, especially when multiple defects are included. The qualitative results and quantitative data are conducive to providing some reference for engineering applications in nondestructive testing and structural health monitoring.