Intelligent fault diagnosis of rotating machinery under variable working conditions based on deep transfer learning with fusion of local and global time–frequency features
Autor(en): |
Xiao Yu
(School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China)
Songcheng Wang (School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China) Hongyang Xu Kun Yu Ke Feng (School of Engineering, University of British Columbia, Kelowna, BC, Canada) Yongchao Zhang (School of Engineering, University of British Columbia, Kelowna, BC, Canada) Xiaowen Liu (School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China) |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Structural Health Monitoring, November 2023, n. 4, v. 23 |
Seite(n): | 2238-2254 |
DOI: | 10.1177/14759217231199427 |
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Datenseite - Reference-ID
10755766 - Veröffentlicht am:
14.01.2024 - Geändert am:
20.09.2024