Semi-supervised gearbox fault diagnosis under variable working conditions based on masked contrastive learning

To address the problem that it is difficult to label variable working condition gearbox fault samples and the significant data distribution discrepancies in practical engineering, which result in reduced accuracy of fault diagnosis models, a semi-supervised gearbox fault diagnosis method based on ma...

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Bibliografske podrobnosti

Principais autores:	ZHANG Huiyun, ZUO Fangjun, LI Hang, YU Xi
Format:	Artigo
Jezik:	Chinês
Izdano:	Editorial Office of Journal of Mechanical Strength 2025-06-01
Serija:	Jixie qiangdu
Teme:	Gearbox Variable working condition Fault diagnosis Contrastive learning Semi-supervised
Online dostop:	http://www.jxqd.net.cn/thesisDetails#DOI：10.16579/j.issn.1001.9669.2025.06.009
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