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
Source PublicationIEEE/CAA Journal of Automatica Sinica
ISSN2329-9266
2023
Volume10Issue:1Pages:121-134
AbstractIn 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.
KeywordAdversarial training data fusion deep learning remaining useful life (RUL) prediction sensor malfunction
DOI10.1109/JAS.2022.105935
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/50731
Collection学术期刊_IEEE/CAA Journal of Automatica Sinica
Recommended Citation
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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