Partial Transfer Learning Method Based on Inter-Class Feature Transfer for Rolling Bearing Fault Diagnosis

Partial Transfer Learning Method Based on Inter-Class Feature Transfer for Rolling Bearing Fault Diagnosis

Rolling bearing fault diagnosis methods based on transfer learning always assume that the sample classes in the target domain are consistent with those in the source domain during the training phase. However, it is difficult to collect all fault classes in the early stage of mechanical application....

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Détails bibliographiques
Auteurs principaux: Hongbo Que, Xuyan Liu, Siqin Jin, Yaoyan Huo, Chengpan Wu, Chuancang Ding, Zhongkui Zhu
Format: Article
Langue:English
Publié: MDPI AG 2024-08-01
Collection:Sensors
Sujets:
fault diagnosis
partial transfer learning
label imbalance
domain adaptation
deep transfer learning
Accès en ligne:https://www.mdpi.com/1424-8220/24/16/5165

Internet

https://www.mdpi.com/1424-8220/24/16/5165

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