A coarse-to-fine bi-level adversarial domain adaptation method for fault diagnosis of rolling bearings

Liu, Z.-H., Chen, L., Wei, H.-L. orcid.org/0000-0002-4704-7346 et al. (3 more authors) (2022) A coarse-to-fine bi-level adversarial domain adaptation method for fault diagnosis of rolling bearings. IEEE Transactions on Instrumentation and Measurement, 71. 3527014. ISSN 0018-9456

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Item Type: Article
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Keywords: Fault diagnosis; rolling bearings; domain adaptation; bi-level adversarial learning; sparse representation; machine learning; deep learning; transfer learning
Dates:
  • Published: 13 October 2022
  • Published (online): 13 October 2022
  • Accepted: 2 October 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 26 Oct 2022 17:25
Last Modified: 25 Sep 2024 14:21
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: 10.1109/tim.2022.3214624
Open Archives Initiative ID (OAI ID):

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