Integrating causal representations with domain adaptation for fault diagnosis

In practical fault diagnosis, obtaining sufficient samples is often challenging. Transfer learning can help by using data from related domains, but significant distribution differences often exist due to different working conditions. To address this issue, cross-domain fault diagnosis (CDFD) has att...

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Veröffentlicht in:	Reliability engineering & system safety Jg. 260; S. 110999
Hauptverfasser:	Jiang, Ming, Zhou, Kuang, Gao, Jiahui, Zhang, Fode
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.08.2025
Schlagworte:	Causal representations Fault diagnosis Invariant representations Transfer learning Fault diagnosis Causal representations Invariant representations Transfer learning
ISSN:	0951-8320
Online-Zugang:	Volltext
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