A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance

doi:10.1109/JAS.2021.1003835

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	A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance
	Chuang Chen; Ningyun Lu; Bin Jiang; Cunsong Wang
刊名	IEEE/CAA Journal of Automatica Sinica
	2021
卷号	8 期号:2 页码:412-422
关键词	Long short-term memory (LSTM) network predictive maintenance remaining useful life (RUL) estimation risk-averse adaptation support vector regression (SVR)
ISSN号	2329-9266
DOI	10.1109/JAS.2021.1003835
英文摘要	Remaining useful life (RUL) prediction is an advanced technique for system maintenance scheduling. Most of existing RUL prediction methods are only interested in the precision of RUL estimation; the adverse impact of over-estimated RUL on maintenance scheduling is not of concern. In this work, an RUL estimation method with risk-averse adaptation is developed which can reduce the over-estimation rate while maintaining a reasonable under-estimation level. The proposed method includes a module of degradation feature selection to obtain crucial features which reflect system degradation trends. Then, the latent structure between the degradation features and the RUL labels is modeled by a support vector regression (SVR) model and a long short-term memory (LSTM) network, respectively. To enhance the prediction robustness and increase its marginal utility, the SVR model and the LSTM model are integrated to generate a hybrid model via three connection parameters. By designing a cost function with penalty mechanism, the three parameters are determined using a modified grey wolf optimization algorithm. In addition, a cost metric is proposed to measure the benefit of such a risk-averse predictive maintenance method. Verification is done using an aero-engine data set from NASA. The results show the feasibility and effectiveness of the proposed RUL estimation method and the predictive maintenance strategy.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/43921]
专题	自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Chuang Chen,Ningyun Lu,Bin Jiang,et al. A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance[J]. IEEE/CAA Journal of Automatica Sinica,2021,8(2):412-422.
APA	Chuang Chen,Ningyun Lu,Bin Jiang,&Cunsong Wang.(2021).A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance.IEEE/CAA Journal of Automatica Sinica,8(2),412-422.
MLA	Chuang Chen,et al."A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance".IEEE/CAA Journal of Automatica Sinica 8.2(2021):412-422.