Li, Guoqiang https://orcid.org/0009-0007-7786-9272
Liu, Qijun
Chen, Zuoyi
Cheng, Yiwei
Wei, Meirong
Wu, Defeng
Funding for this research was provided by:
The Natural Science Foundation of Fujian under Grant (2024J08064)
key laboratory of marine power engineering technology of ministry of transport (KLMPET2023-02)
Natural Science Foundation of Xiamen (3502Z202471042)
Article Title: Intelligent fault diagnosis of rotating machinery driven by physical information and contrastive learning under extreme sample imbalance conditions
Journal Title: Measurement Science and Technology
Article Type: paper
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Publication dates
Date Received: 2025-07-26
Date Accepted: 2025-10-09
Online publication date: 2025-10-28