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基于竞争失效的综合传动剩余寿命预测

Translated title of the contribution: Remaining Useful Life Prediction of Power-Shift Steering Transmission Based on Competing Failures
  • Beijing Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Translated title of the contributionRemaining Useful Life Prediction of Power-Shift Steering Transmission Based on Competing Failures
Original languageChinese (Traditional)
Pages (from-to)426-431 and 461
JournalQiche Gongcheng/Automotive Engineering
Volume41
Issue number4
DOIs
Publication statusPublished - 25 Apr 2019

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