Prediction and Abnormality Assertion on Emu Brake Pad Based on Multivariate Integrated Random Walk

Abstract

To better solve the issue with abnormal failure of electric motor unit (EMU) brake pad resulted from various random factors in the ever-changing operating environment, in this paper, a new evaluation method of performance prediction and abnormity decision is proposed based on the Multivariate integrated random walk (MIRW) model. In this method, the state space model of the EMU brake pad performance degradation is firstly established. And then based on the observed data, the brake pad performance degradation trend is extracted by the fixed interval forward - backward smoothing algorithm. Based on it, the future degradation state can be predicted by Kalman predictor. Based on the obtained state estimation values, abnormal failure tolerance range (AFTR) can be determined applying Grubbs criterion to judge whether the brake pad is being in abnormal state before reaching the final failure or not as a new sample appears. In addition, the cumulative failure probability of the brake pad is estimated in the degradation process. Finally, the thickness data of a certain type of EMU brake pad is applied to predict the future degradation state and determine the abnormal condition, and the result shows that the proposed method is more efficient and accurate.