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OpenAlex Citation Counts

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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:

Machinery fault diagnosis with imbalanced data using deep generative adversarial networks
Zhang We, Xiang Li, Xiaodong Jia, et al.
Measurement (2019) Vol. 152, pp. 107377-107377
Closed Access | Times Cited: 299

Showing 1-25 of 299 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
Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study
Zhibin Zhao, Tianfu Li, Jingyao Wu, et al.
ISA Transactions (2020) Vol. 107, pp. 224-255
Open Access | Times Cited: 426
Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions
Tianci Zhang, Jinglong Chen, Fudong Li, et al.
ISA Transactions (2021) Vol. 119, pp. 152-171
Closed Access | Times Cited: 368
Fault detection of wind turbine based on SCADA data analysis using CNN and LSTM with attention mechanism
Ling Xiang, Penghe Wang, Xin Yang, et al.
Measurement (2021) Vol. 175, pp. 109094-109094
Closed Access | Times Cited: 268
Federated learning for machinery fault diagnosis with dynamic validation and self-supervision
Zhang We, Xiang Li, Hui Ma, et al.
Knowledge-Based Systems (2020) Vol. 213, pp. 106679-106679
Closed Access | Times Cited: 224
Universal Domain Adaptation in Fault Diagnostics With Hybrid Weighted Deep Adversarial Learning
Zhang We, Xiang Li, Hui Ma, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 17, Iss. 12, pp. 7957-7967
Closed Access | Times Cited: 206
Open-Set Domain Adaptation in Machinery Fault Diagnostics Using Instance-Level Weighted Adversarial Learning
Zhang We, Xiang Li, Hui Ma, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 17, Iss. 11, pp. 7445-7455
Closed Access | Times Cited: 185
A double-layer attention based adversarial network for partial transfer learning in machinery fault diagnosis
Yafei Deng, Delin Huang, Shichang Du, et al.
Computers in Industry (2021) Vol. 127, pp. 103399-103399
Closed Access | Times Cited: 178
Deep Learning-Based Partial Domain Adaptation Method on Intelligent Machinery Fault Diagnostics
Xiang Li, Zhang We
IEEE Transactions on Industrial Electronics (2020) Vol. 68, Iss. 5, pp. 4351-4361
Closed Access | Times Cited: 169
Data synthesis using deep feature enhanced generative adversarial networks for rolling bearing imbalanced fault diagnosis
Shaowei Liu, Hongkai Jiang, Zhenghong Wu, et al.
Mechanical Systems and Signal Processing (2021) Vol. 163, pp. 108139-108139
Closed Access | Times Cited: 166
Deep learning-based prognostic approach for lithium-ion batteries with adaptive time-series prediction and on-line validation
Zhang We, Xiang Li, Xu Li
Measurement (2020) Vol. 164, pp. 108052-108052
Closed Access | Times Cited: 162
A Gentle Introduction to Reinforcement Learning and its Application in Different Fields
Muddasar Naeem, Syed Tahir Hussain Rizvi, Antonio Coronato
IEEE Access (2020) Vol. 8, pp. 209320-209344
Open Access | Times Cited: 154
Data alignments in machinery remaining useful life prediction using deep adversarial neural networks
Xiang Li, Zhang We, Hui Ma, et al.
Knowledge-Based Systems (2020) Vol. 197, pp. 105843-105843
Closed Access | Times Cited: 147
Federated Transfer Learning for Intelligent Fault Diagnostics Using Deep Adversarial Networks With Data Privacy
Zhang We, Xiang Li
IEEE/ASME Transactions on Mechatronics (2021) Vol. 27, Iss. 1, pp. 430-439
Closed Access | Times Cited: 146
Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study
Omar AlShorman, Fahad Alkahatni, Mahmoud Masadeh, et al.
Advances in Mechanical Engineering (2021) Vol. 13, Iss. 2
Closed Access | Times Cited: 139
Deep representation clustering-based fault diagnosis method with unsupervised data applied to rotating machinery
Xiang Li, Xu Li, Hui Ma
Mechanical Systems and Signal Processing (2020) Vol. 143, pp. 106825-106825
Closed Access | Times Cited: 137
Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions
Zhang We, Xiang Li, Hui Ma, et al.
Reliability Engineering & System Safety (2021) Vol. 211, pp. 107556-107556
Closed Access | Times Cited: 130
Data Augmentation and Intelligent Fault Diagnosis of Planetary Gearbox Using ILoFGAN Under Extremely Limited Samples
Mingzhi Chen, Haidong Shao, Haoxuan Dou, et al.
IEEE Transactions on Reliability (2022) Vol. 72, Iss. 3, pp. 1029-1037
Open Access | Times Cited: 127
A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation
Azal Ahmad Khan, Omkar Chaudhari, Rohitash Chandra
Expert Systems with Applications (2023) Vol. 244, pp. 122778-122778
Open Access | Times Cited: 116
Normalized Conditional Variational Auto-Encoder with adaptive Focal loss for imbalanced fault diagnosis of Bearing-Rotor system
Xiaoli Zhao, Jianyong Yao, Wenxiang Deng, et al.
Mechanical Systems and Signal Processing (2022) Vol. 170, pp. 108826-108826
Closed Access | Times Cited: 114
Adaptive variational autoencoding generative adversarial networks for rolling bearing fault diagnosis
Xin Wang, Hongkai Jiang, Zhenghong Wu, et al.
Advanced Engineering Informatics (2023) Vol. 56, pp. 102027-102027
Closed Access | Times Cited: 98
A Systematic Review on Imbalanced Learning Methods in Intelligent Fault Diagnosis
Zhijun Ren, Tantao Lin, Ke Feng, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-35
Closed Access | Times Cited: 87
Imbalanced bearing fault diagnosis under variant working conditions using cost-sensitive deep domain adaptation network
Zhenyu Wu, Hongkui Zhang, Juchuan Guo, et al.
Expert Systems with Applications (2022) Vol. 193, pp. 116459-116459
Closed Access | Times Cited: 83
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
A bearing fault diagnosis method without fault data in new working condition combined dynamic model with deep learning
Kun Xu, Xianguang Kong, Qibin Wang, et al.
Advanced Engineering Informatics (2022) Vol. 54, pp. 101795-101795
Closed Access | Times Cited: 69
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