Deep Reconstruction Transfer Convolutional Neural Network for Rolling Bearing Fault Diagnosis

Deep transfer learning has been widely used to improve the versatility of models. In the problem of cross-domain fault diagnosis in rolling bearings, most models require that the given data have a similar distribution, which limits the diagnostic effect and generalization of the model. This paper pr...

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Autori principali:	Ziwei Feng, Qingbin Tong, Xuedong Jiang, Feiyu Lu, Xin Du, Jianjun Xu, Jingyi Huo
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2024-03-01
Serie:	Sensors
Soggetti:	intelligent fault diagnosis transfer learning domain adaptation autoencoder label smoothing
Accesso online:	https://www.mdpi.com/1424-8220/24/7/2079
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