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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:

An intelligent fault diagnosis framework dealing with arbitrary length inputs under different working conditions
Zenghui An, Shunming Li, Yu Xin, et al.
Measurement Science and Technology (2019) Vol. 30, Iss. 12, pp. 125107-125107
Closed Access | Times Cited: 26

Showing 1-25 of 26 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
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: 329
Novel Joint Transfer Network for Unsupervised Bearing Fault Diagnosis From Simulation Domain to Experimental Domain
Yiming Xiao, Haidong Shao, Song-Yu Han, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 27, Iss. 6, pp. 5254-5263
Closed Access | Times Cited: 225
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: 59
An intelligent diagnosis framework for roller bearing fault under speed fluctuation condition
Baokun Han, Shanshan Ji, Jinrui Wang, et al.
Neurocomputing (2020) Vol. 420, pp. 171-180
Closed Access | Times Cited: 68
Condition Monitoring of Rail Transport Systems: A Bibliometric Performance Analysis and Systematic Literature Review
Mariusz Kostrzewski, Rafał Melnik
Sensors (2021) Vol. 21, Iss. 14, pp. 4710-4710
Open Access | Times Cited: 42
Intelligent Diagnostics for Ball Screw Fault Through Indirect Sensing Using Deep Domain Adaptation
Vibhor Pandhare, Xiang Li, Marcella Miller, et al.
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 70, pp. 1-11
Closed Access | Times Cited: 40
Technology development and commercial applications of industrial fault diagnosis system: a review
Chengze Liu, A. Cichoń, Grzegorz Królczyk, et al.
The International Journal of Advanced Manufacturing Technology (2021) Vol. 118, Iss. 11-12, pp. 3497-3529
Open Access | Times Cited: 35
Data augment method for machine fault diagnosis using conditional generative adversarial networks
Jinrui Wang, Baokun Han, Huaiqian Bao, et al.
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering (2020) Vol. 234, Iss. 12, pp. 2719-2727
Closed Access | Times Cited: 37
A New Fuzzy Logic Classifier Based on Multiscale Permutation Entropy and Its Application in Bearing Fault Diagnosis
Wenhua Du, Xiaoming Guo, Zhijian Wang, et al.
Entropy (2019) Vol. 22, Iss. 1, pp. 27-27
Open Access | Times Cited: 28
Simulation Data-driven Enhanced Unsupervised Domain Adaptation for Bearing Fault Diagnosis
Haidong Shao, Yiming Xiao, Shen Yan
Journal of Mechanical Engineering (2023) Vol. 59, Iss. 3, pp. 76-76
Open Access | Times Cited: 8
Deep Adaptive Adversarial Network-Based Method for Mechanical Fault Diagnosis under Different Working Conditions
Jinrui Wang, Shanshan Ji, Baokun Han, et al.
Complexity (2020) Vol. 2020, pp. 1-11
Open Access | Times Cited: 21
A Fault Diagnosis Method Based on a Rainbow Recursive Plot and Deep Convolutional Neural Networks
Xiaoyuan Wang, Xin Wang, Tianyuan Li, et al.
Energies (2023) Vol. 16, Iss. 11, pp. 4357-4357
Open Access | Times Cited: 6
A novel transfer-learning method based on selective normalization for fault diagnosis with limited labeled data
Xiao Zhang, Baokun Han, Jinrui Wang, et al.
Measurement Science and Technology (2021) Vol. 32, Iss. 10, pp. 105116-105116
Closed Access | Times Cited: 14
Rolling Bearing Fault Diagnosis Based on Domain Adaptation and Preferred Feature Selection under Variable Working Conditions
Xiao Yu, Wei Chen, Chuanlong Wu, et al.
Shock and Vibration (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 13
Acoustic Monitoring of Railway Defects Using Deep Learning with Audio to Spectrogram Conversion
Emre Uygun, Serdal Terzi
Journal of Vibration Engineering & Technologies (2023) Vol. 12, Iss. 2, pp. 2585-2594
Closed Access | Times Cited: 5
An improved two-stream compression convolution network for rolling bearing fault diagnosis
Hailong Jin, Wuxu Ma, Zong Meng, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 12, pp. 125110-125110
Closed Access | Times Cited: 6
Spindle thermal error modeling method considering the operating condition based on Long Short-Term Memory
Yu Chen, Huicheng Zhou, Jihong Chen, et al.
Engineering Research Express (2021) Vol. 3, Iss. 3, pp. 035019-035019
Open Access | Times Cited: 8
A new transferable bearing fault diagnosis approach with adaptive manifold embedded distribution alignment
Piao Lei, Changqing Shen, Jun Zhu, et al.
Measurement Science and Technology (2020)
Closed Access | Times Cited: 6
Technical Language Supervision for Intelligent Fault Diagnosis in Process Industry
Karl Löwenmark, Cees Taal, Stephan Schnabel, et al.
International Journal of Prognostics and Health Management (2022) Vol. 13, Iss. 2
Open Access | Times Cited: 3
Intelligent Fault Diagnosis Across Varying Working Conditions Using Triplex Transfer LSTM for Enhanced Generalization
Misbah Iqbal, C.K.M. Lee, K. L. Keung, et al.
Mathematics (2024) Vol. 12, Iss. 23, pp. 3698-3698
Open Access
Bidirectional Shrinkage Gated Recurrent Unit Network With Multiscale Attention Mechanism for Multisensor Fault Diagnosis
Gang Wang, Yanmei Li, Yifei Wang, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 20, pp. 25518-25533
Closed Access | Times Cited: 1
Unsupervised transfer learning for intelligent health status identification of bearing in adaptive input length selection
Guiting Tang, Lei Liu, Yirong Liu, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107051-107051
Closed Access | Times Cited: 1
Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition
Shiyuan Liu, Xiao Yu, Qian Xu, et al.
Shock and Vibration (2020) Vol. 2020, pp. 1-34
Open Access | Times Cited: 1
Fault recognition of rolling bearing with small-scale dataset based on transfer learning
Ying Wang, Mingxuan Liang, Xiangwei Wu, et al.
Journal of Vibroengineering (2021) Vol. 23, Iss. 5, pp. 1160-1170
Open Access | Times Cited: 1
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