Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

A New Deep Transfer Learning Method for Bearing Fault Diagnosis Under Different Working Conditions
Jun Zhu, Nan Chen, Changqing Shen
IEEE Sensors Journal (2019) Vol. 20, Iss. 15, pp. 8394-8402
Closed Access | Times Cited: 220

Showing 1-25 of 220 citing articles:

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Weihua Li, Ruyi Huang, Jipu Li, et al.
Mechanical Systems and Signal Processing (2021) Vol. 167, pp. 108487-108487
Open Access | Times Cited: 523
Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook
Ricardo Silva Peres, Xiaodong Jia, Jay Lee, et al.
IEEE Access (2020) Vol. 8, pp. 220121-220139
Open Access | Times Cited: 426
A comprehensive review on convolutional neural network in machine fault diagnosis
Jinyang Jiao, Ming Zhao, Jing Lin, et al.
Neurocomputing (2020) Vol. 417, pp. 36-63
Open Access | Times Cited: 403
A systematic review of deep transfer learning for machinery fault diagnosis
Chuan Li, Shaohui Zhang, Qin Yi, et al.
Neurocomputing (2020) Vol. 407, pp. 121-135
Closed Access | Times Cited: 348
Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study
Zhibin Zhao, Qiyang Zhang, Xiaolei Yu, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-28
Open Access | Times Cited: 325
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Laith Alzubaidi, Jinshuai Bai, Aiman Al-Sabaawi, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 320
Intelligent fault diagnosis of machinery using digital twin-assisted deep transfer learning
Min Xia, Haidong Shao, Darren L. Williams, et al.
Reliability Engineering & System Safety (2021) Vol. 215, pp. 107938-107938
Open Access | Times Cited: 263
Multi-scale deep intra-class transfer learning for bearing fault diagnosis
Xu Wang, Changqing Shen, Min Xia, et al.
Reliability Engineering & System Safety (2020) Vol. 202, pp. 107050-107050
Open Access | Times Cited: 252
A New Multiple Source Domain Adaptation Fault Diagnosis Method Between Different Rotating Machines
Jun Zhu, Nan Chen, Changqing Shen
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 7, pp. 4788-4797
Closed Access | Times Cited: 147
A systematic review of rolling bearing fault diagnoses based on deep learning and transfer learning: Taxonomy, overview, application, open challenges, weaknesses and recommendations
Mohammed Hakim, Abdoulhdi A. Borhana Omran, Ali Najah Ahmed, et al.
Ain Shams Engineering Journal (2022) Vol. 14, Iss. 4, pp. 101945-101945
Open Access | Times Cited: 129
A multi-source information transfer learning method with subdomain adaptation for cross-domain fault diagnosis
Jinghui Tian, Dongying Han, Mengdi Li, et al.
Knowledge-Based Systems (2022) Vol. 243, pp. 108466-108466
Closed Access | Times Cited: 113
Fully interpretable neural network for locating resonance frequency bands for machine condition monitoring
Dong Wang, Yikai Chen, Changqing Shen, et al.
Mechanical Systems and Signal Processing (2021) Vol. 168, pp. 108673-108673
Closed Access | Times Cited: 108
A survey of transfer learning for machinery diagnostics and prognostics
Siya Yao, Qi Kang, MengChu Zhou, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 4, pp. 2871-2922
Closed Access | Times Cited: 74
Fault diagnosis in rotating machines based on transfer learning: Literature review
Iqbal Misbah, C.K.M. Lee, K. L. Keung
Knowledge-Based Systems (2023) Vol. 283, pp. 111158-111158
Closed Access | Times Cited: 57
A knowledge dynamic matching unit-guided multi-source domain adaptation network with attention mechanism for rolling bearing fault diagnosis
Zhenghong Wu, Hongkai Jiang, Hongxuan Zhu, et al.
Mechanical Systems and Signal Processing (2023) Vol. 189, pp. 110098-110098
Closed Access | Times Cited: 50
A new adaptive multi-scale attention adversarial network for cross-domain fault diagnosis
Lingtan Kong, Jinrui Wang, Dawei Wang, et al.
Knowledge-Based Systems (2025), pp. 113066-113066
Closed Access | Times Cited: 1
Universal federated domain adaptation for gearbox fault diagnosis: A robust framework for credible pseudo-label generation
Xinyu Ren, Suixin Wang, Wanli Zhao, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103233-103233
Closed Access | Times Cited: 1
A Deep Adversarial Transfer Learning Network for Machinery Emerging Fault Detection
Jipu Li, Ruyi Huang, Guolin He, et al.
IEEE Sensors Journal (2020) Vol. 20, Iss. 15, pp. 8413-8422
Closed Access | Times Cited: 104
Transfer learning-based strategies for fault diagnosis in building energy systems
Jiangyan Liu, Qing Zhang, Xin Li, et al.
Energy and Buildings (2021) Vol. 250, pp. 111256-111256
Closed Access | Times Cited: 96
Light neural network with fewer parameters based on CNN for fault diagnosis of rotating machinery
Tongtong Jin, Chuliang Yan, Chuanhai Chen, et al.
Measurement (2021) Vol. 181, pp. 109639-109639
Closed Access | Times Cited: 91
Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Majdi Mansouri, Mohamed Trabelsi, Hazem Nounou, et al.
IEEE Access (2021) Vol. 9, pp. 126286-126306
Open Access | Times Cited: 86
Similarity-based meta-learning network with adversarial domain adaptation for cross-domain fault identification
Yong Feng, Jinglong Chen, Zhuozheng Yang, et al.
Knowledge-Based Systems (2021) Vol. 217, pp. 106829-106829
Closed Access | Times Cited: 80
Moment matching-based intraclass multisource domain adaptation network for bearing fault diagnosis
Yu Xia, Changqing Shen, Dong Wang, et al.
Mechanical Systems and Signal Processing (2021) Vol. 168, pp. 108697-108697
Closed Access | Times Cited: 77
Rotating machinery fault detection and diagnosis based on deep domain adaptation: A survey
Siyu Zhang, Lei Su, Jiefei Gu, et al.
Chinese Journal of Aeronautics (2021) Vol. 36, Iss. 1, pp. 45-74
Open Access | Times Cited: 73
Cross-Domain Open-Set Machinery Fault Diagnosis Based on Adversarial Network With Multiple Auxiliary Classifiers
Jun Zhu, Cheng‐Geng Huang, Changqing Shen, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 18, Iss. 11, pp. 8077-8086
Closed Access | Times Cited: 70
Page 1 - Next Page

Scroll to top