Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks

doi:10.1109/JAS.2022.105935

CASIA OpenIR > 学术期刊 > IEEE/CAA Journal of Automatica Sinica

	Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks
	Xiang Li; Yixiao Xu; Naipeng Li; Bin Yang; Yaguo Lei
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2023
卷号	10 期号:1 页码:121-134
摘要	In recent years, intelligent data-driven prognostic methods have been successfully developed, and good machinery health assessment performance has been achieved through explorations of data from multiple sensors. However, existing data-fusion prognostic approaches generally rely on the data availability of all sensors, and are vulnerable to potential sensor malfunctions, which are likely to occur in real industries especially for machines in harsh operating environments. In this paper, a deep learning-based remaining useful life (RUL) prediction method is proposed to address the sensor malfunction problem. A global feature extraction scheme is adopted to fully exploit information of different sensors. Adversarial learning is further introduced to extract generalized sensor-invariant features. Through explorations of both global and shared features, promising and robust RUL prediction performance can be achieved by the proposed method in the testing scenarios with sensor malfunctions. The experimental results suggest the proposed approach is well suited for real industrial applications.
关键词	Adversarial training data fusion deep learning remaining useful life (RUL) prediction sensor malfunction
DOI	10.1109/JAS.2022.105935
引用统计	被引频次：56[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50731
专题	学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Xiang Li,Yixiao Xu,Naipeng Li,et al. Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(1):121-134.
APA	Xiang Li,Yixiao Xu,Naipeng Li,Bin Yang,&Yaguo Lei.(2023).Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks.IEEE/CAA Journal of Automatica Sinica,10(1),121-134.
MLA	Xiang Li,et al."Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks".IEEE/CAA Journal of Automatica Sinica 10.1(2023):121-134.

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