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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:

QSCGAN: An Un-Supervised Quick Self-Attention Convolutional GAN for LRE Bearing Fault Diagnosis Under Limited Label-Lacked Data
Wenqing Wan, Shuilong He, Jinglong Chen, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-16
Closed Access | Times Cited: 49

Showing 1-25 of 49 citing articles:

Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
Haixin Lv, Jinglong Chen, Tongyang Pan, et al.
Measurement (2022) Vol. 199, pp. 111594-111594
Closed Access | Times Cited: 148
Leveraging Generative Adversarial Networks for Data Augmentation to Improve Fault Detection in Wind Turbines with Imbalanced Data
Subhajit Chatterjee, Yung-Cheol Byun
Results in Engineering (2025), pp. 103991-103991
Open Access | Times Cited: 2
Small sample fault diagnosis method for wind turbine gearbox based on optimized generative adversarial networks
Yuanhao Su, Liang Meng, Xiaojia Kong, et al.
Engineering Failure Analysis (2022) Vol. 140, pp. 106573-106573
Closed Access | Times Cited: 51
Full Attention Wasserstein GAN With Gradient Normalization for Fault Diagnosis Under Imbalanced Data
Jigang Fan, Xianfeng Yuan, Zhaoming Miao, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-16
Closed Access | Times Cited: 48
Fault Diagnosis Method Based on Two-Stage GAN for Data Imbalance
Wei Luo, Wei Yang, Jialong He, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 22, pp. 21961-21973
Closed Access | Times Cited: 42
ICoT-GAN: Integrated Convolutional Transformer GAN for Rolling Bearings Fault Diagnosis Under Limited Data Condition
Huihui Gao, Xiaoran Zhang, Xuejin Gao, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-14
Closed Access | Times Cited: 31
An Intelligent Method for Early Motor Bearing Fault Diagnosis Based on Wasserstein Distance Generative Adversarial Networks Meta Learning
Peien Luo, Zhonggang Yin, Dongsheng Yuan, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 23
Fault diagnosis of wind turbine gearbox under limited labeled data through temporal predictive and similarity contrast learning embedded with self-attention mechanism
Yunyi Zhu, Bin Xie, Anqi Wang, et al.
Expert Systems with Applications (2023) Vol. 245, pp. 123080-123080
Closed Access | Times Cited: 22
CBAM-CRLSGAN: A novel fault diagnosis method for planetary transmission systems under small samples scenarios
Jie Zhang, Yun Kong, Zhuyun Chen, et al.
Measurement (2024) Vol. 234, pp. 114795-114795
Closed Access | Times Cited: 13
Rotating Machinery Fault Diagnosis with Limited Multisensor Fusion Samples by Fused Attention-Guided Wasserstein GAN
Wenlong Fu, Ke Yang, Bin Wen, et al.
Symmetry (2024) Vol. 16, Iss. 3, pp. 285-285
Open Access | Times Cited: 11
Time series diffusion method: A denoising diffusion probabilistic model for vibration signal generation
Haiming Yi, Lei Hou, Yuhong Jin, et al.
Mechanical Systems and Signal Processing (2024) Vol. 216, pp. 111481-111481
Open Access | Times Cited: 10
A bearing fault diagnosis method with an improved residual Unet diffusion model under extreme data imbalance
Huaqing Wang, Wenbo Zhang, Changkun Han, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046113-046113
Closed Access | Times Cited: 9
Generative artificial intelligence and data augmentation for prognostic and health management: Taxonomy, progress, and prospects
Shen Liu, Jinglong Chen, Yong Feng, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124511-124511
Closed Access | Times Cited: 8
Imbalance fault diagnosis under long-tailed distribution: Challenges, solutions and prospects
Zhuohang Chen, Jinglong Chen, Yong Feng, et al.
Knowledge-Based Systems (2022) Vol. 258, pp. 110008-110008
Closed Access | Times Cited: 35
Self-Supervised Simple Siamese Framework for Fault Diagnosis of Rotating Machinery With Unlabeled Samples
Wenqing Wan, Jinglong Chen, Zitong Zhou, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 35, Iss. 5, pp. 6380-6392
Closed Access | Times Cited: 29
Limited Fault Data Augmentation With Compressed Sensing for Bearing Fault Diagnosis
Dongdong Wang, Yining Dong, Han Wang, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 13, pp. 14499-14511
Closed Access | Times Cited: 21
A review: the application of generative adversarial network for mechanical fault diagnosis
Weiqing Liao, Ke Yang, Wenlong Fu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 062002-062002
Closed Access | Times Cited: 7
Mdrs-Gan: A Multi-Scale Dense Residual Shrinkage Generative Adversarial Network for Rotating Machinery Fault Diagnosis Under Limited Data
Tongqiang Yi, Jiang Guo, Fang Yuan, et al.
(2025)
Closed Access
Generative Adversarial Networks for Gearbox of Wind Turbine With Unbalanced Data Sets in Fault Diagnosis
Yuanhao Su, Liang Meng, Xiaojia Kong, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 13, pp. 13285-13298
Closed Access | Times Cited: 24
MIM-Graph: A multi-sensor network approach for fault diagnosis of HSR Bogie bearings at the IoT edge via mutual information maximization
Wenqing Wan, Jinglong Chen, Jingsong Xie
ISA Transactions (2023) Vol. 139, pp. 574-585
Closed Access | Times Cited: 13
Multi-task Learning for Aero-engine Bearing Fault Diagnosis with Limited Data
Peixuan Ding, Yi Xu, Xi‐Ming Sun
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-11
Closed Access | Times Cited: 4
Data Augmentation Fault Diagnosis Method Based on Residual Mixed Self-Attention for Rolling Bearings Under Imbalanced Samples
Jiuyuan Huo, Chenbo Qi, Chaojie Li, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-14
Closed Access | Times Cited: 11
Improved Generative Adversarial Networks With Filtering Mechanism for Fault Data Augmentation
Lexuan Shao, Ningyun Lu, Bin Jiang, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 13, pp. 15176-15187
Closed Access | Times Cited: 10
Compound fault diagnosis of rolling bearings with few-shot based on DCGAN-RepLKNet
Hongze Zhu, Ting Fang
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066105-066105
Open Access | Times Cited: 3
Privacy‐preserving gradient boosting tree: Vertical federated learning for collaborative bearing fault diagnosis
Liqiao Xia, Pai Zheng, Jinjie Li, et al.
IET Collaborative Intelligent Manufacturing (2022) Vol. 4, Iss. 3, pp. 208-219
Open Access | Times Cited: 14
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