A novel hierarchical physical-guided crack monitoring framework for metallic plates: A virtual transferable baseline approach

While guided wave detection has been addressed successfully in composite panels, its application to metallic plates remains considerably more challenging because wave propagation in metallic structures is fundamentally different and the presence of a crack further complicates the behavior. As a result, a novel multi-stage framework for crack identification is presented, combining tip-induced diffraction with detailed Lamb wave analysis. The method proceeds through detection, localization, and characterization, ensuring accurate evaluation of crack presence, orientation, and severity. A virtual baseline is reconstructed using shapelets extracted from Lamb wave signals via physical-guided K-SVD dictionary learning, effectively eliminating the need for prior baseline data and improving the robustness of GWSHM under varying conditions. Notably, the framework enables detailed crack characterization using only sparse sensors, which is considerably more challenging than simple damage detection or localization in guided wave based SHM. The framework begins with a crack detection stage, in which a reliability-based threshold is established to confirm the presence of crack and suppress false alarms. Once detection is confirmed, crack localization is achieved through a fusion imaging algorithm that estimates the crack position with high precision. Subsequently, a time-of-flight–based tip estimation technique is employed to distinguish tip diffractions from specular reflections, allowing accurate identification of both crack tips and enabling continuous monitoring of crack growth. The proposed framework has been experimentally validated on both artificial cracks and naturally developed notches generated using an Instron 250 kN hydraulic fatigue machine, demonstrating adaptability under diverse defect scenarios and loading conditions. Overall, by integrating virtual baseline reconstruction, reliability threshold analysis, crack imaging technique, weak-amplitude diffraction isolation, this study establishes a systematic methodology that substantially enhances the reliability and accuracy of long-term crack detection, localization, and characterization in GWSHM.