Intelligent fault diagnosis of machinery using digital twin-assisted deep transfer learning

•A methodology for fault diagnosis with limited available data is achieved.•A digital twin of the machine is used to provide fault condition data for pre-training.•One-shot learning is achieved with the proposed deep transfer learning method.•Activation function and cost function of the deep network...

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Vydané v:	Reliability engineering & system safety Ročník 215; s. 107938
Hlavní autori:	Xia, Min, Shao, Haidong, Williams, Darren, Lu, Siliang, Shu, Lei, de Silva, Clarence W.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Barking Elsevier Ltd 01.11.2021 Elsevier BV
Predmet:	Coders Deep transfer learning Digital twin Digital twins Domains Fault diagnosis Learning Novel sparse de-noising auto-encoder Reliability engineering Transfer learning Working conditions Fault diagnosis Digital twin Novel sparse de-noising auto-encoder Deep transfer learning
ISSN:	0951-8320, 1879-0836
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