Liu, Tao
Shen, Changqing https://orcid.org/0000-0002-5143-8366
Qi, Yumei
Wang, Jiaan https://orcid.org/0000-0002-2107-2877
Cai, Junsong
Zhu, Zhongkui
Funding for this research was provided by:
Suzhou Science Foundation (SYG202323)
Natural Science Foundation of the Jiangsu Higher Education Institutions (22KJD460006)
National Natural Science Foundation of China (52272440)
Article Title: Domain-invariant feature learning based on a curvature-sensitive regulation strategy for bearing fault diagnosis under variable working conditions
Journal Title: Measurement Science and Technology
Article Type: paper
Copyright Information: © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Publication dates
Date Received: 2024-11-05
Date Accepted: 2025-05-01
Online publication date: 2025-05-09