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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:

Digital twin aided adversarial transfer learning method for domain adaptation fault diagnosis
Jinrui Wang, Zongzhen Zhang, Zhiliang Liu, et al.
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109152-109152
Closed Access | Times Cited: 86

Showing 1-25 of 86 citing articles:

A novel digital twin-driven approach based on physical-virtual data fusion for gearbox fault diagnosis
Jingyan Xia, Ruyi Huang, Zhuyun Chen, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109542-109542
Closed Access | Times Cited: 54
A novel domain generalization network with multidomain specific auxiliary classifiers for machinery fault diagnosis under unseen working conditions
Rui Wang, Weiguo Huang, Yixiang Lu, et al.
Reliability Engineering & System Safety (2023) Vol. 238, pp. 109463-109463
Open Access | Times Cited: 44
Digital twin-assisted imbalanced fault diagnosis framework using subdomain adaptive mechanism and margin-aware regularization
Shen Yan, Xiang Zhong, Haidong Shao, et al.
Reliability Engineering & System Safety (2023) Vol. 239, pp. 109522-109522
Open Access | Times Cited: 44
Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery
Shengnan Tang, Jingtao Ma, Zhengqi Yan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108678-108678
Closed Access | Times Cited: 32
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: 18
Few-shot fault diagnosis of axial piston pump based on prior knowledge-embedded meta learning vision transformer under variable operating conditions
Suiyan Wang, Hanqin Shuai, Junhui Hu, et al.
Expert Systems with Applications (2025) Vol. 269, pp. 126452-126452
Closed Access | Times Cited: 8
Digital twin-based gearbox fault diagnosis using variational mode decomposition and dynamic vibration modeling
Houssem Habbouche, Yassine Amirat, Tarak Benkedjouh, et al.
Measurement (2025) Vol. 246, pp. 116669-116669
Closed Access | Times Cited: 2
A novel generalized source-free domain adaptation approach for cross-domain industrial fault diagnosis
Jilun Tian, Jiusi Zhang, Yuchen Jiang, et al.
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109891-109891
Closed Access | Times Cited: 33
Digital twins-based process monitoring for wastewater treatment processes
Wentao Liu, Sudao He, Jianpeng Mou, et al.
Reliability Engineering & System Safety (2023) Vol. 238, pp. 109416-109416
Closed Access | Times Cited: 27
Semi-supervised ensemble fault diagnosis method based on adversarial decoupled auto-encoder with extremely limited labels
Congying Deng, Zihao Deng, Jianguo Miao
Reliability Engineering & System Safety (2023) Vol. 242, pp. 109740-109740
Closed Access | Times Cited: 26
Dynamic model-assisted transferable network for liquid rocket engine fault diagnosis using limited fault samples
Chenxi Wang, Yuxiang Zhang, Zhibin Zhao, et al.
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109837-109837
Closed Access | Times Cited: 26
Semi-supervised meta-path space extended graph convolution network for intelligent fault diagnosis of rotating machinery under time-varying speeds
Ying Li, Lijie Zhang, Pengfei Liang, et al.
Reliability Engineering & System Safety (2024) Vol. 251, pp. 110363-110363
Closed Access | Times Cited: 15
A digital twin-driven approach for partial domain fault diagnosis of rotating machinery
Jingyan Xia, Zhuyun Chen, Jiaxian Chen, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107848-107848
Closed Access | Times Cited: 14
A dynamic collaborative adversarial domain adaptation network for unsupervised rotating machinery fault diagnosis
Xin Wang, Hongkai Jiang, Mu Mingzhe, et al.
Reliability Engineering & System Safety (2024), pp. 110662-110662
Closed Access | Times Cited: 11
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: 9
SRSGCN: A novel multi-sensor fault diagnosis method for hydraulic axial piston pump with limited data
Pengfei Liang, Xiangfeng Wang, Chao Ai, et al.
Reliability Engineering & System Safety (2024) Vol. 253, pp. 110563-110563
Closed Access | Times Cited: 9
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
Digital twin-driven focal modulation-based convolutional network for intelligent fault diagnosis
Sheng Li, Qiubo Jiang, Yadong Xu, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109590-109590
Closed Access | Times Cited: 19
A novel sample selection approach based universal unsupervised domain adaptation for fault diagnosis of rotating machinery
Biliang Lu, Yingjie Zhang, Zhaohua Liu, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109618-109618
Closed Access | Times Cited: 18
Digital twin-driven prognostics and health management for industrial assets
Bin Xiao, Jingshu Zhong, Xiangyu Bao, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
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: 7
Digital twin-assisted AI framework based on domain adaptation for bearing defect diagnosis in the centrifugal pump
Anil Kumar, Rajesh Kumar, Jiawei Xiang, et al.
Measurement (2024) Vol. 235, pp. 115013-115013
Closed Access | Times Cited: 7
Spatial-temporal graph feature learning driven by time–frequency similarity assessment for robust fault diagnosis of rotating machinery
Lei Wang, Fuchen Xie, Xin Zhang, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102711-102711
Closed Access | Times Cited: 7
A Finite Element Model of an Electric Motor with an Unbalanced Rotor for Vibration Data Generation
Hyun-Seung Lee, Seho Son, Dayeon Jeong, et al.
International Journal of Precision Engineering and Manufacturing-Smart Technology (2024) Vol. 2, Iss. 1, pp. 47-56
Open Access | Times Cited: 6
Reinforced fuzzy domain adaptation: Revolutionizing data-unaccessible rotating machinery fault diagnosis across multiple domains
Zongkai Liu, Ke Zhao, Haidong Shao, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124094-124094
Closed Access | Times Cited: 6
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