Learning the health index of complex systems using dynamic conditional variational autoencoders

Recent advances in sensing technologies have enabled engineers to collect big data to predict the remaining useful life (RUL) of complex systems. Current modeling techniques for RUL predictions are usually not able to quantify the degradation behavior of a complex system through a health index. Alth...

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Veröffentlicht in:	Reliability engineering & system safety Jg. 216; S. 108004
Hauptverfasser:	Wei, Yupeng, Wu, Dazhong, Terpenny, Janis
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Barking Elsevier Ltd 01.12.2021 Elsevier BV
Schlagworte:	Complex systems Data fusion Deep learning Degradation Degradation modeling Multiple sensors Reliability engineering Remaining useful life Deep learning Data fusion Multiple sensors Remaining useful life Degradation modeling
ISSN:	0951-8320, 1879-0836
Online-Zugang:	Volltext
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