Signal Processing Analysis of Lamb Wave Propagation in Stainless Steel Plates with Thickness Defects: Implications for AI-Based Non-Destructive Testing

This study investigates the interaction of Lamb waves with defects in a 304 stainless steel plate using numerical simulations in the commercial software Abaqus. We model four different configurations: a healthy plate, a plate with a single-sided 10% thickness loss, a plate with a 30% thickness loss, and a plate with symmetrical 10 % thickness loss on both sides. Lamb wave propagation is excited at 2100 kHz.mm, focusing on the A0 mode. Using 2D Fast Fourier Transform (2D-FFT) analysis, we compare analytical dispersion curves with those obtained numerically, examining incident, transmitted, and reflected modes across different defect scenarios.The results reveal that defect size and symmetry significantly influence mode conversion, reflection, and transmission, especially for the A0 and A1 modes. Larger defects lead to stronger interactions, while symmetrical defects show distinct transmission and reflection patterns compared to single-sided losses.These findings provide valuable insights into guided wave behavior in the presence of defects and offer a foundation for developing robust datasets. Such datasets have the potential to be used in AI-based non-destructive testing (NDT) applications, facilitating automated defect detection and structural health monitoring. This work contributes to the advancement of both traditional and AI-enhanced NDT methods, aiming to improve defect detection accuracy and efficiency in critical engineering structures.