Fourier-domain beamforming for Full Matrix Capture Data with Circular Statistics Vector Weighting in Nondestructive Testing

Abstract

Abstract Total focusing method (TFM) based on full-matrix capture (FMC) is widely used in the field of nondestructive testing due to its high resolution and high signal-to-noise ratio. In order to solve the problems of the slow speed of traditional time-domain total focusing imaging and poor imaging quality, this paper proposes a total focusing imaging method weighted by circular statistics vector (CSV) in the Fourier domain (FD). Firstly, the cosine and sinusoidal components of the instantaneous phase in the undelayed RF signal are extracted, and the coherence factor is established according to the cosine and sinusoidal components in the FD domain. Finally, the total focusing image in the FD domain is weighted. The complexity calculation shows that CSV-weighted imaging in the FD domain has a higher imaging speed than delay-and-sum (DAS) imaging. The DAS total focusing imaging algorithm, FD domain total focusing imaging algorithm, and FD domain CSV weighted imaging algorithm are used to verify the hole and crack defects in brass test blocks, aluminum test blocks, and steel test blocks. The experimental results show that the proposed FD domain CSV weighted imaging map generally shows higher resolution and signal-to-noise ratio, and the algorithm has higher robustness. Also, it has revealed a low computational load.