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Remaining Useful Life Prediction of Power-Shift Steering Transmission Based on Competing Failures
Yan Shufa, Ma Biao , Zheng Changsong
2019, 41 (4 ):
426-431.
doi: 10.19562/j.chinasae.qcgc.2019.04.010
Remaining useful life(RUL) prediction is the key issue to fault diagnosis and health management of mechanical transmission system. As a complex time-varying electromechanical system, the power-shift steering transmission (PSST) often has many failure modes and processes in the running process under high speed and heavy load, and the interaction between different failure modes is competition failure. However, in current RUL prediction studies of PSST, there is no study considering the competing failure. In this paper, the RUL prediction method of PSST is presented based on competing risks of degradation failure and random failure. First, the multi-dimensional degradation monitoring data is integrated by the state space model and robust kernel principle component analysis (PCA) to obtain the degradation index of the whole machine. Then, the degradation model is established based on Wiener process, the random failure model is established based on Weibull distribution, and the competition failure model of PSST is further established considering the correlation between the degradation failure and random failure. Finally, the model's parameters are estimated by the maximum likelihood estimation (EML) method and the RUL prediction of PSST is realized. The experiments validate the proposed method, and the results indicate that the proposed method can objectively describe the reliability variation law of the device and can effectively improve the accuracy of RUL prediction.
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