EMAT-Enhanced Synthetic Aperture Imaging With Phase-Sensitive Dual-Mode Signal Processing for Defect Characterization in Nondestructive Testing

To enhance the accuracy of electromagnetic ultrasonic defect imaging, this study proposes a dual-wave defect signal phase feature recognition (DDFR) algorithm based on a sandwich-structured dual-wave electromagnetic acoustic transducer (EMAT). The algorithm integrates amplitude and phase information from longitudinal and shear waves to achieve precise extraction of defect signals. The dual-wave EMAT employs a sandwich structure design, with its beam focusing capability and detection sensitivity improved through multiphysics coupling analysis and Nelder-Mead algorithm-based parameter optimization. Four defects were detected using the dual-wave EMAT, and the acquired signals were processed using the DDFR algorithm. Imaging was performed via a simplified delay-and-sum synthetic aperture imaging. Results demonstrate that the study effectively identifies and locates all four defects, with a positioning error of less than 1 mm. This study provides an effective imaging solution for electromagnetic ultrasonic defect detection and imaging.