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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:

Maximum mean square discrepancy: A new discrepancy representation metric for mechanical fault transfer diagnosis
Quan Qian, Yi Wang, Taisheng Zhang, et al.
Knowledge-Based Systems (2023) Vol. 276, pp. 110748-110748
Closed Access | Times Cited: 82

Showing 1-25 of 82 citing articles:

Inverse physics–informed neural networks for digital twin–based bearing fault diagnosis under imbalanced samples
Yi Qin, Hongyu Liu, Yi Wang, et al.
Knowledge-Based Systems (2024) Vol. 292, pp. 111641-111641
Closed Access | Times Cited: 30
An uncertainty perception metric network for machinery fault diagnosis under limited noisy source domain and scarce noisy unknown domain
Changdong Wang, Jingli Yang, Huamin Jie, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102682-102682
Closed Access | Times Cited: 30
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
Variance discrepancy representation: A vibration characteristic-guided distribution alignment metric for fault transfer diagnosis
Quan Qian, Huayan Pu, Tianjia Tu, et al.
Mechanical Systems and Signal Processing (2024) Vol. 217, pp. 111544-111544
Closed Access | Times Cited: 19
A two-stage importance-aware subgraph convolutional network based on multi-source sensors for cross-domain fault diagnosis
Yue Yu, Youqian He, Hamid Reza Karimi, et al.
Neural Networks (2024) Vol. 179, pp. 106518-106518
Open Access | Times Cited: 18
Self-paced decentralized federated transfer framework for rotating machinery fault diagnosis with multiple domains
Ke Zhao, Zhenbao Liu, Jia Li, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111258-111258
Closed Access | Times Cited: 17
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
FEV-Swin: Multi-source heterogeneous information fusion under a variant swin transformer framework for intelligent cross-domain fault diagnosis
Keyi Zhou, Keyi Zhou, Bin Jiang, et al.
Knowledge-Based Systems (2025), pp. 112982-112982
Closed Access | Times Cited: 2
Dynamics modeling of faulty planetary gearboxes by time-varying mesh stiffness excitation of spherical overlapping pittings
Yi Qin, Qirui Li, Shuo Wang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 210, pp. 111162-111162
Closed Access | Times Cited: 14
Domain adaptive learning based on equilibrium distribution and dynamic subspace approximation
Zhonghua Liu, Tiansheng Wang, Fa Zhu, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123673-123673
Closed Access | Times Cited: 14
Multi-scale residual neural network with enhanced gated recurrent unit for fault diagnosis of rolling bearing
Weiqing Liao, Wenlong Fu, Ke Yang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056114-056114
Closed Access | Times Cited: 11
A deep targeted transfer network with clustering pseudo-label learning for fault diagnosis across different Machines
Feiyu Lu, Qingbin Tong, Xuedong Jiang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 213, pp. 111344-111344
Closed Access | Times Cited: 11
Fault vibration model driven fault-aware domain generalization framework for bearing fault diagnosis
Bin Pang, Qiuhai Liu, Zhenli Xu, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102620-102620
Closed Access | Times Cited: 11
Heterogeneous Federated Domain Generalization Network With Common Representation Learning for Cross-Load Machinery Fault Diagnosis
Quan Qian, Jun Luo, Yi Qin
IEEE Transactions on Systems Man and Cybernetics Systems (2024) Vol. 54, Iss. 9, pp. 5704-5716
Closed Access | Times Cited: 10
Federated transfer learning for machinery fault diagnosis: A comprehensive review of technique and application
Quan Qian, Bin Zhang, Chuan Li, et al.
Mechanical Systems and Signal Processing (2024) Vol. 223, pp. 111837-111837
Closed Access | Times Cited: 10
FTSDC: A novel federated transfer learning strategy for bearing cross-machine fault diagnosis based on dual-correction training
Zhenhao Yan, Zifeng Xu, Yixiang Zhang, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102499-102499
Closed Access | Times Cited: 9
A roadmap to fault diagnosis of industrial machines via machine learning: A brief review
Govind Vashishtha, Sumika Chauhan, Mert Sehri, et al.
Measurement (2024) Vol. 242, pp. 116216-116216
Closed Access | Times Cited: 9
Like draws to like: A Multi-granularity Ball-Intra Fusion approach for fault diagnosis models to resists misleading by noisy labels
Fir Dunkin, Xinde Li, Chuanfei Hu, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102425-102425
Closed Access | Times Cited: 8
Multi-source partial domain adaptation method based on pseudo-balanced target domain for fault diagnosis
Guowei Zhang, Xianguang Kong, Qibin Wang, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111255-111255
Closed Access | Times Cited: 16
Imbalanced deep transfer network for fault diagnosis of high-speed train traction motor bearings
Yilong Liu, Xinyuan Li, Xingwu Zhang, et al.
Knowledge-Based Systems (2024) Vol. 293, pp. 111682-111682
Closed Access | Times Cited: 6
Domain adaptation with domain specific information and feature disentanglement for bearing fault diagnosis
Shaozhang Xie, Peng Xia, Hanqi Zhang
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056101-056101
Open Access | Times Cited: 5
Federated temporal-context contrastive learning for fault diagnosis using multiple datasets with insufficient labels
Haowen Zheng, Hui Liu, Zhenyu Liu, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102432-102432
Closed Access | Times Cited: 5
Cloud-edge collaborative transfer fault diagnosis of rotating machinery via federated fine-tuning and target self-adaptation
Rui Wang, Weiguo Huang, Yixiang Lu, et al.
Expert Systems with Applications (2024) Vol. 250, pp. 123859-123859
Closed Access | Times Cited: 5
Large Model for Rotating Machine Fault Diagnosis Based on a Dense Connection Network With Depthwise Separable Convolution
Yi Qin, Taisheng Zhang, Quan Qian, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-12
Closed Access | Times Cited: 5
Envelope spectrum neural network with adaptive domain weight harmonization for intelligent bearing fault diagnosis under cross-machine scenarios
Feiyu Lu, Qingbin Tong, Xuedong Jiang, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102787-102787
Closed Access | Times Cited: 5
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