Chen, Hongming
Meng, Wei
Li, Yongjian https://orcid.org/0000-0001-5570-9242
Xiong, Qing https://orcid.org/0000-0002-7267-2784
Funding for this research was provided by:
Natural Science Foundation of Sichuan Province (No. 2022 NSFSC0400)
Opening Project of The State Key Laboratory of Heavy Duty AC Drive Electric Locomotive Systems Integration (No. 2020ZJKF05)
Article Title: An anti-noise fault diagnosis approach for rolling bearings based on multiscale CNN-LSTM and a deep residual learning model
Journal Title: Measurement Science and Technology
Article Type: paper
Copyright Information: © 2023 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Publication dates
Date Received: 2022-10-10
Date Accepted: 2023-01-05
Online publication date: 2023-01-30