OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Multiscale Residual Antinoise Network via Interpretable Dynamic Recalibration Mechanism for Rolling Bearing Fault Diagnosis With Few Samples
Bin Liu, Changfeng Yan, Yaofeng Liu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 24, pp. 31425-31439
Closed Access | Times Cited: 7
Bin Liu, Changfeng Yan, Yaofeng Liu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 24, pp. 31425-31439
Closed Access | Times Cited: 7
Showing 7 citing articles:
Interpretable physics-informed domain adaptation paradigm for cross-machine transfer diagnosis
Chao He, Hongmei Shi, Xiaorong Liu, et al.
Knowledge-Based Systems (2024) Vol. 288, pp. 111499-111499
Closed Access | Times Cited: 20
Chao He, Hongmei Shi, Xiaorong Liu, et al.
Knowledge-Based Systems (2024) Vol. 288, pp. 111499-111499
Closed Access | Times Cited: 20
Interpretable modulated differentiable STFT and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine transfer fault diagnosis under speed fluctuations
Chao He, Hongmei Shi, Ruixin Li, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102568-102568
Open Access | Times Cited: 17
Chao He, Hongmei Shi, Ruixin Li, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102568-102568
Open Access | Times Cited: 17
ISEANet: An interpretable subdomain enhanced adaptive network for unsupervised cross-domain fault diagnosis of rolling bearing
Bin Liu, Changfeng Yan, Yaofeng Liu, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102610-102610
Closed Access | Times Cited: 10
Bin Liu, Changfeng Yan, Yaofeng Liu, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102610-102610
Closed Access | Times Cited: 10
A frequency channel-attention based vision Transformer method for bearing fault identification across different working conditions
Ling Xiang, Hankun Bing, Xianze Li, et al.
Expert Systems with Applications (2024) Vol. 262, pp. 125686-125686
Closed Access | Times Cited: 3
Ling Xiang, Hankun Bing, Xianze Li, et al.
Expert Systems with Applications (2024) Vol. 262, pp. 125686-125686
Closed Access | Times Cited: 3
A novel method based on the SCNGO‐ICEEMDAN and MCNN‐BiLSTM model for fault diagnosis of motor bearings for more electric aircraft
Dongsheng Yuan, Feng Liu, Zhonggang Yin, et al.
IET Electric Power Applications (2024)
Open Access
Dongsheng Yuan, Feng Liu, Zhonggang Yin, et al.
IET Electric Power Applications (2024)
Open Access
Dual-feature enhanced hybrid convolutional network for imbalanced fault diagnosis of rolling bearings
Yingjie Zhao, Changfeng Yan, Bin Liu, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 016023-016023
Open Access
Yingjie Zhao, Changfeng Yan, Bin Liu, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 016023-016023
Open Access
A hybrid deep learning network for diagnosing multipoint faults in rolling bearings under variable operating conditions
Y. Huang, Changfeng Yan, Bin Liu, et al.
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 11, pp. 5989-6003
Closed Access
Y. Huang, Changfeng Yan, Bin Liu, et al.
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 11, pp. 5989-6003
Closed Access
