A fault diagnosis method for power generation rotating machinery based on small-sample augmentation and dilated residual network
Crossref DOI link: https://doi.org/10.1186/s44147-026-01125-0
Published Online: 2026-07-09
Published Print: 2026-12
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Wang, Lipeng https://orcid.org/0000-0002-3398-7628
Ge, Junchao
Text and Data Mining valid from 2026-07-09
Version of Record valid from 2026-07-09
Article History
Received: 10 May 2026
Accepted: 2 July 2026
First Online: 9 July 2026
Declarations
:
: The authors declare that they have no competing interests.