Least-squares reverse time migration for flaw characterisation using ultrasonic bulk waves

Accurate detection and characterization of flaws are very important in the assessment of structural integrity of critical structures in aerospace and nuclear industry. In this paper, an effective ultrasonic imaging technique based on least-squares reverse time migration (LSRTM) is developed for imaging flaws. Reverse time migration (RTM) is a powerful wave-equation-based approach and it has the ability to account for rapid spatial velocity variations and to utilize all wavefront information. It is based on cross-correlating the forward wavefield with the back-propagated wavefield scattered from flaws. To achieve images with better quality, the solution can be obtained by iteratively finding an image generating the modeled data which can best match the measured data in a least-squares sense, i.e. least-squares migration (LSM). Combining RTM and LSM, the LSRTM algorithm is applied to the measured data from the virtual experiment and the physical laboratory experiment, and the results show high-quality reconstructed images for flaw identification.