Critical welded structures in rail vehicles are subjected to prolonged alternating loads, making structural fatigue failure a primary safety concern. This study develops a quantitative crack diagnosis technology based on piezoelectric intelligent layer sensing. Through integrated simulation of weld structures and piezoelectric sensing, we investigate the coupling mechanism between piezoelectric wave signals and crack propagation, and design a comprehensive system architecture for real-time crack monitoring. Ground validation tests were conducted on typical welded specimens with incrementally introduced cracks. The combined simulation and experimental approach demonstrates the feasibility of quantitative diagnosis technology for weld structures, providing a robust framework for enhancing railway safety. • This study develops an integrated simulation–experiment framework based on a piezoelectric smart layer for real-time monitoring and quantitative diagnosis of cracks in critical welded structures of rail vehicles. The work systematically investigates the coupling mechanism between ultrasonic Lamb waves and crack defects, and proposes a dedicated structural health monitoring (SHM) system architecture. • Ground tests were conducted on representative welded specimens with artificially introduced cracks of varying sizes. The experimental results demonstrate the system’s ability to detect and quantify crack growth through signal feature evolution. • The combination of finite element simulation and experimental validation confirms the feasibility and accuracy of the proposed quantitative diagnostic approach, providing a reliable basis for early crack detection and integrity assessment of in-service rail vehicle welds.
Wang et al. (Sun,) studied this question.