Zhuyun Chen

6.1k total citations · 10 hit papers
104 papers, 4.7k citations indexed

About

Zhuyun Chen is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Zhuyun Chen has authored 104 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Control and Systems Engineering, 51 papers in Mechanical Engineering and 26 papers in Mechanics of Materials. Recurrent topics in Zhuyun Chen's work include Machine Fault Diagnosis Techniques (67 papers), Fault Detection and Control Systems (26 papers) and Gear and Bearing Dynamics Analysis (21 papers). Zhuyun Chen is often cited by papers focused on Machine Fault Diagnosis Techniques (67 papers), Fault Detection and Control Systems (26 papers) and Gear and Bearing Dynamics Analysis (21 papers). Zhuyun Chen collaborates with scholars based in China, Belgium and Hong Kong. Zhuyun Chen's co-authors include Weihua Li, Konstantinos Gryllias, Ruyi Huang, Jipu Li, Guolin He, Yixiao Liao, Alexandre Mauricio, Jiaxian Chen, Ruqiang Yan and Jingyan Xia and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Zhuyun Chen

87 papers receiving 4.6k citations

Hit Papers

Multisensor Feature Fusion for Bearing Fault Diagnosis Us... 2017 2026 2020 2023 2017 2021 2020 2019 2019 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zhuyun Chen China 30 3.6k 2.1k 1.2k 1.0k 381 104 4.7k
Saibo Xing China 11 3.4k 0.9× 2.0k 1.0× 1.2k 1.0× 711 0.7× 299 0.8× 13 4.0k
Te Han China 32 3.1k 0.9× 1.7k 0.8× 917 0.8× 826 0.8× 314 0.8× 90 4.4k
Long Wen China 25 3.2k 0.9× 1.8k 0.8× 951 0.8× 986 1.0× 748 2.0× 78 4.9k
René–Vinicio Sánchez Ecuador 30 3.2k 0.9× 2.1k 1.0× 1.2k 1.0× 517 0.5× 379 1.0× 112 4.3k
Konstantinos Gryllias Belgium 29 3.1k 0.9× 2.0k 0.9× 1.0k 0.9× 658 0.7× 232 0.6× 136 4.1k
Siyu Shao China 15 2.7k 0.8× 1.5k 0.7× 861 0.7× 611 0.6× 374 1.0× 27 3.6k
Changqing Shen China 41 5.6k 1.6× 3.4k 1.6× 1.8k 1.6× 1.1k 1.1× 361 0.9× 199 6.8k
Zhongkui Zhu China 39 3.8k 1.1× 2.4k 1.2× 1.2k 1.1× 561 0.6× 256 0.7× 168 4.7k
Min Xia China 29 2.5k 0.7× 1.6k 0.7× 886 0.8× 657 0.7× 541 1.4× 112 4.4k

Countries citing papers authored by Zhuyun Chen

Since Specialization
Citations

This map shows the geographic impact of Zhuyun Chen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zhuyun Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhuyun Chen more than expected).

Fields of papers citing papers by Zhuyun Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhuyun Chen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zhuyun Chen. The network helps show where Zhuyun Chen may publish in the future.

Co-authorship network of co-authors of Zhuyun Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Zhuyun Chen. A scholar is included among the top collaborators of Zhuyun Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zhuyun Chen. Zhuyun Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhang, Bin, et al.. (2025). Virtual-real twin data powered deep adaptive detection method for corrosion damage in cable aluminum sheath structure using helical guided waves. Engineering Structures. 333. 120195–120195. 1 indexed citations
3.
Li, Jipu, et al.. (2024). A relationship-aware calibrated prototypical network for fault incremental diagnosis of electric motors without reserved samples. Reliability Engineering & System Safety. 252. 110429–110429. 10 indexed citations
5.
Lin, Huibin, Ding Li, Jipu Li, et al.. (2024). A novel gearbox local fault feature extraction method based on quality coefficient and dictionary learning. Measurement Science and Technology. 35(6). 65112–65112. 4 indexed citations
6.
Li, Jipu, et al.. (2024). An auto-regulated universal domain adaptation network for uncertain diagnostic scenarios of rotating machinery. Expert Systems with Applications. 249. 123836–123836. 18 indexed citations
7.
Ma, Shuai, Jiewu Leng, Pai Zheng, et al.. (2024). A digital twin-assisted deep transfer learning method towards intelligent thermal error modeling of electric spindles. Journal of Intelligent Manufacturing. 36(3). 1659–1688. 24 indexed citations
8.
Zhang, Jie, Yun Kong, Zhuyun Chen, et al.. (2024). CBAM-CRLSGAN: A novel fault diagnosis method for planetary transmission systems under small samples scenarios. Measurement. 234. 114795–114795. 20 indexed citations
9.
Xia, Jingyan, Ruyi Huang, Jipu Li, Zhuyun Chen, & Weihua Li. (2024). Digital Twin-Assisted Fault Diagnosis of Rotating Machinery Without Measured Fault Data. IEEE Transactions on Instrumentation and Measurement. 73. 1–10. 32 indexed citations
11.
Wang, Rugen, Zhuyun Chen, & Weihua Li. (2023). Gradient flow-based meta generative adversarial network for data augmentation in fault diagnosis. Applied Soft Computing. 142. 110313–110313. 24 indexed citations
12.
Liu, Feifei, et al.. (2023). Dynamic characteristics modeling and optimization for hydraulic engine mounts based on deep neural network coupled with genetic algorithm. Engineering Applications of Artificial Intelligence. 130. 107683–107683. 5 indexed citations
13.
Chen, Zhuyun, Jingyan Xia, Jipu Li, et al.. (2023). Generalized open-set domain adaptation in mechanical fault diagnosis using multiple metric weighting learning network. Advanced Engineering Informatics. 57. 102033–102033. 88 indexed citations breakdown →
14.
Wang, Rugen, Zhuyun Chen, & Weihua Li. (2023). Normal Sinkhorn Distance: A novel metric for evaluating generated signals and its application in mechanical fault diagnosis. Mechanical Systems and Signal Processing. 198. 110449–110449. 4 indexed citations
15.
Chen, Jiaxian, Ruyi Huang, Zhuyun Chen, Wentao Mao, & Weihua Li. (2023). Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective. Mechanical Systems and Signal Processing. 193. 110239–110239. 149 indexed citations breakdown →
16.
Huang, Ruyi, Jingyan Xia, Bin Zhang, Zhuyun Chen, & Weihua Li. (2023). Compound Fault Diagnosis for Rotating Machinery: State-of-the-Art, Challenges, and Opportunities. 57 indexed citations
17.
Yang, Xiaoqing, et al.. (2023). Improved Vibration Signal Models of Localized Faults of Sun Gears to Predict Modulation. Symmetry. 15(9). 1621–1621. 1 indexed citations
18.
Chen, Zhuyun, Yixiao Liao, Jipu Li, et al.. (2022). A Multi-Source Weighted Deep Transfer Network for Open-Set Fault Diagnosis of Rotary Machinery. IEEE Transactions on Cybernetics. 53(3). 1982–1993. 148 indexed citations breakdown →
19.
Liao, Yixiao, Ruyi Huang, Jipu Li, Zhuyun Chen, & Weihua Li. (2021). Correction to: Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis. Chinese Journal of Mechanical Engineering. 34(1). 6 indexed citations
20.
Liao, Yixiao, Ruyi Huang, Jipu Li, Zhuyun Chen, & Weihua Li. (2021). Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis. Chinese Journal of Mechanical Engineering. 34(1). 24 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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