Early Track Disease Diagnosis Based on Wavelet Analysis of Vehicle Vibration Response

From the perspective of real-time performance and cost-effectiveness in the early diagnosis of high-speed railway track defects, this study proposes a track anomaly diagnosis method based on wavelet analysis of operational train vibration acceleration responses. Firstly, a train model was established using SIMPACK software with the CRH380-BG EMU as the prototype. Based on statistical information of track defects, three typical types of track defect irregularities with different wavelengths and waveforms were constructed. The amplitude of the early-stage defects was set and added to the track irregularity spectrum as an external excitation. The acceleration response of the train bogie when passing through a section with early-stage defects was obtained, and this data was used to verify the feasibility of diagnosing early-stage track defects based on wavelet analysis of train vibration responses. The research results show that the acceleration response of the train bogie alone cannot directly diagnose early-stage track defects with small damage amplitudes, but the high-frequency reconstructed signals obtained from the wavelet decomposition of the bogie acceleration exhibit significant mutations at the defect locations, enabling accurate localization of abnormal time points and achieving the diagnosis of early-stage track defects, and they can also achieve synchronous detection of multiple types of track damage anomalies.