A fast imaging algorithm for internal metal defects with zero group velocity energy anomalies based on laser ultrasonic dynamic ridge tracking

Abstract In response to the challenges of low sensitivity and low efficiency in traditional laser ultrasonic detection methods when detecting micro-defects in metal components, this study proposes a rapid imaging method for internal metal defects based on zero group velocity (ZGV) energy anomalies. This approach extracts the time-frequency characteristics of ZGV signals by tracking laser ultrasonic time-frequency ridges, utilizing the energy anomaly metrics of ZGV signals to detect defects. The three-dimensional finite element model of laser ultrasonics demonstrates the mechanism of Lamb wave propagation and ZGV formation in defective plate structures, revealing significant local energy concentration induced by acoustic impedance discontinuities at defect sites. This confirms the correlation between energy distribution and defect characteristics. Experimental validation through a non-contact laser ultrasonic detection system verifies the algorithm's capability to reduce spatial sampling density. When the sampling interval approximates defect dimensions, it reconstructs two-dimensional contours; when exceeding defect size, it enables rapid coarse defect localization imaging—maintaining detection efficacy even at measurement point intervals over 5 times the defect size. This provides an effective strategy for efficient and accurate internal defect detection in metal components.