High-resolution ultrasonic imaging of the defects in coarse-grained steel by a weighted total focusing method

Ultrasonic testing of coarse-grained materials is strongly influenced by high-level scattering noise. In addition, the signal-to-noise ratio (SNR) and spatial resolution of imaging by the traditional total focusing method (TFM) are relatively low. In this study, we focused on the reconstruction of high-resolution ultrasonic images from full matrix capture datasets. A weighted TFM image by combining the inverse problem-based method and traditional TFM is proposed to detect defects in coarse-grained steel. The proposed method was used to image defects with the full matrix data obtained through simulations and experiments. The simulation and experimental results show that the weighted total focusing method can significantly improve the SNR of ultrasonic imaging in coarse-grained steel and, moreover, it can improve the resolution of imaging and distinguish adjacent defects with a centre distance less than the Rayleigh criteria.