Dynamic Identification of Micro-Damage Evolution Using Ultrasonic Guided Wave Monitoring Method

Large-scale damage often originates from minor deterioration, making the dynamic identification of the micro-damage evolution trend critical. In this paper, a composite feature extraction method (CFEM) of ultrasonic guided wave (GUW) monitoring is proposed. First, the window transient energy (WTE) is extracted through a sliding window, followed by the steady energy index (SEI) matrix calculation. Then, by analyzing the characteristics of micro-damage evolution processes, two special criteria are advanced, leading to the definition of steady energy growth index (SEGI) and steady energy ratio index (SERI). Finally, the composite damage index (CDI) and dynamic damage index (DDI) are computed to analyze these micro-damage evolution trends. A simulation model was established to analyze the physical basis of the method. This paper primarily focuses on fatigue cracks, a typical example of micro-damage, and conducts fatigue loading tests on switch rails, as these have a significant impact. A total of 253 thousand fatigue loading cycles were executed from the onset of the experiment until the fracture of the switch rail. It was determined that CFEM was able to identify micro-damage earlier and more stably compared to the other two methods in relate works. The application of CFEM is not restricted to rails, it also proves beneficial for other components such as pipes, plates, and rods.