关键词: 列车故障, 横向减振器, 经验模式分解, 排列组合熵, ReliefF

Abstract: Lateral damper is the key part of bogie, its role is to reduce vibration between train body and bogie, its performance has important influence on the comfort and safety of the train. The fault of lateral damper will change vibration signal of train body. In order to monitor its performance and fault diagnosis, this paper proposes a fault diagnosis method of high speed train bogie based on EMD permutation entropy and ReliefF. Vibration signals at different positions of train are obtained by experiment. Firstly, preprocessing signal is decomposed by EMD, then the entropy value of IMFs that include main fault information is calculated. At last, it applies ReliefF on optimizing and dimension reduction of characteristic vector constituted by six IMFs, SVM method is used to identify faults. Using support vector machine to recognize four working conditions. The experimental results show that the average recognition rate can reach more than 96% when the speed is equal or greater than 200 km/h.

Key words: train fault, lateral damper, empirical mode decomposition, permutation entropy, ReliefF