Research On The Life Prediction Model Of Critical Components Of EMU Based On Real-Time Monitoring

With the development of China’s high-speed rail, especially in recent years, Beijing-Shanghai, Wuhan-Guangzhou, Guangzhou-Shenzhen, Harbin-Dalian and so on high-speed railways have opened, EMU becomes increasingly importance in passenger and freight railway transport.The brake pad is an important part of bogie which is one of the key components of EMU, directly relating to the state traffic safety. Based on the real wear data and the research of brake pads, this paper deeply researches the wear of brake pads. Through the study of the gray model and BP neural network model, combination model with the two is optimized further. And a new brake pad life prediction model is established. With MATLAB programming, it simplifies the solving process model. Finally, validating with multiple sets of data, we have achieved good prediction effect. Compared to the traditional model, the combination model after optimization improves the accuracy by about4%. The average prediction accuracy for the ten set of data is more than98%, this prediction can be applied to the actual. The research results of this study will provide some reference for our EMU brake pad life prediction.