Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing

Fault diagnosis of rolling bearings has attracted extensive attention in industrial fields, which plays a vital role in guaranteeing the reliability, safety, and economical efficiency of mechanical systems. Traditional data-driven fault diagnosis methods require obtaining a dataset of full failure m...

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Vydané v:	Reliability engineering & system safety Ročník 234; s. 109186
Hlavní autori:	Zhang, Yongchao, Ji, J.C., Ren, Zhaohui, Ni, Qing, Gu, Fengshou, Feng, Ke, Yu, Kun, Ge, Jian, Lei, Zihao, Liu, Zheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.06.2023
Predmet:	Digital twin Domain adaptation Fault diagnosis Rolling bearing Transformer Fault diagnosis Domain adaptation Transformer Digital twin Rolling bearing
ISSN:	0951-8320, 1879-0836
On-line prístup:	Získať plný text
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