Feibin Zhang

697 total citations · 1 hit paper
25 papers, 505 citations indexed

About

Feibin Zhang is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Feibin Zhang has authored 25 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Control and Systems Engineering, 9 papers in Mechanical Engineering and 6 papers in Mechanics of Materials. Recurrent topics in Feibin Zhang's work include Machine Fault Diagnosis Techniques (17 papers), Fault Detection and Control Systems (10 papers) and Gear and Bearing Dynamics Analysis (7 papers). Feibin Zhang is often cited by papers focused on Machine Fault Diagnosis Techniques (17 papers), Fault Detection and Control Systems (10 papers) and Gear and Bearing Dynamics Analysis (7 papers). Feibin Zhang collaborates with scholars based in China, United Kingdom and Cyprus. Feibin Zhang's co-authors include Jinfeng Huang, Lingli Cui, Fulei Chu, Zhaoye Qin, Xu Wang, Tim Coombs, Shengnan Zhao, Xueyi Li, Xiangwei Kong and David He and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Access and Journal of Sound and Vibration.

In The Last Decade

Feibin Zhang

20 papers receiving 494 citations

Hit Papers

Double attention-guided tree-inspired grade decision netw... 2025 2026 2025 5 10 15 20 25
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Double attention-guided tree-inspired grade decision network: A method for bearing fault diagnosis of unbalanced samples under strong noise conditions
    2025 26 citations Zhilin Dong, Yonghua Jiang et al. Advanced Engineering Informatics profile →

Peers

Feibin Zhang
Zhilin Dong China
Zhiqiang Liao China
Qiuyu Song China
Qiuyang Zhou China
David Verstraete United States
Xiaohui Gu China
Diwang Ruan China
Weigang Wen China
Jianping Yan China
Zhilin Dong China
Feibin Zhang
Citations per year, relative to Feibin Zhang Feibin Zhang (= 1×) peers Zhilin Dong

Countries citing papers authored by Feibin Zhang

Since Specialization
Citations

This map shows the geographic impact of Feibin Zhang'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 Feibin Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feibin Zhang more than expected).

Fields of papers citing papers by Feibin Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Feibin Zhang. 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 Feibin Zhang. The network helps show where Feibin Zhang may publish in the future.

Co-authorship network of co-authors of Feibin Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Feibin Zhang. A scholar is included among the top collaborators of Feibin Zhang 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 Feibin Zhang. Feibin Zhang 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.
Li, Hua, Tianyang Wang, Feibin Zhang, & Fulei Chu. (2025). FMDPgram: An Improvement of FMD for Rotating Machinery Fault Diagnosis. IEEE Transactions on Industrial Informatics. 21(8). 6398–6409.
2.
Li, Hua, Tianyang Wang, Feibin Zhang, & Fulei Chu. (2025). SVD Theory for Machine Fault Detection: A Review. IEEE Sensors Journal. 25(5). 7896–7915.
3.
Li, Hua, Tianyang Wang, Feibin Zhang, & Fulei Chu. (2025). VMDPgram: An Effective Signal Decomposition Method for Rolling Bearing Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement. 74. 1–10.
4.
Li, Mengdi, Jinfeng Huang, Feibin Zhang, et al.. (2025). MSIF-Convformer: a novel end-to-end fault diagnosis framework with multi-source sensors under strong noise. Information Fusion. 129. 104000–104000. 1 indexed citations
5.
Li, Mengdi, Peiming Shi, Jinfeng Huang, Feibin Zhang, & Fulei Chu. (2025). Weak signal detection based on high dimensional space coupled piecewise bistable stochastic resonance. Measurement Science and Technology. 36(6). 66141–66141. 3 indexed citations
6.
Dong, Zhilin, Yonghua Jiang, Weidong Jiao, et al.. (2025). Double attention-guided tree-inspired grade decision network: A method for bearing fault diagnosis of unbalanced samples under strong noise conditions. Advanced Engineering Informatics. 64. 103004–103004. 26 indexed citations breakdown →
7.
8.
Li, Xueyi, et al.. (2024). A fault diagnosis method with AT-ICNN based on a hybrid attention mechanism and improved convolutional layers. Applied Acoustics. 225. 110191–110191. 21 indexed citations
9.
Zheng, Jinde, et al.. (2024). Intelligent fault identification in sample imbalance scenarios using robust low-rank matrix classifier with fuzzy weighting factor. Applied Soft Computing. 152. 111229–111229. 9 indexed citations
10.
Huang, Jinfeng, et al.. (2024). The flexible tensor singular value decomposition and its applications in multisensor signal fusion processing. Mechanical Systems and Signal Processing. 220. 111662–111662. 41 indexed citations
11.
Li, Hua, Tianyang Wang, Feibin Zhang, & Fulei Chu. (2024). AutoVMDPgram: An Effective Method for Fault Diagnosis of Rolling Bearing. IEEE Transactions on Neural Networks and Learning Systems. 36(8). 15233–15243.
12.
Li, Hua, Tianyang Wang, Feibin Zhang, & Fulei Chu. (2024). Enhanced adaptive high-frequency resonance technology for bearing fault detection. Structural Health Monitoring. 23(6). 3430–3445. 4 indexed citations
13.
Ma, Hong, et al.. (2024). Adaptive Embedded Flexible Tensor Singular Spectrum Decomposition. Electronics. 14(1). 21–21. 1 indexed citations
14.
Li, Mengdi, Jinfeng Huang, Peiming Shi, et al.. (2024). A secondary optimization strategy in stochastic resonance modelling for the detection of unknown bearing faults. Chaos Solitons & Fractals. 189. 115576–115576. 6 indexed citations
15.
Zhang, Feibin, Yanliang Wang, Tongtong Liu, et al.. (2024). Adaptive variable sampling T-SSD algorithm. Structural Health Monitoring. 24(6). 3396–3414. 2 indexed citations
16.
Huang, Jinfeng, et al.. (2024). MFSFormer: A Novel End-to-End Rotating Machinery Fault Diagnosis Framework for Noise and Small Samples. IEEE Transactions on Reliability. 74(3). 4158–4169. 4 indexed citations
17.
Zhang, Feibin, et al.. (2024). Mixed style network based: A novel rotating machinery fault diagnosis method through batch spectral penalization. Reliability Engineering & System Safety. 255. 110667–110667. 22 indexed citations
18.
Huang, Jinfeng, Feibin Zhang, Tim Coombs, & Fulei Chu. (2024). The first-kind flexible tensor SVD: innovations in multi-sensor data fusion processing. Nonlinear Dynamics. 113(7). 6541–6559. 15 indexed citations
19.
20.
Cui, Lingli, et al.. (2015). Quantitative diagnosis of fault severity trend of rolling element bearings. Chinese Journal of Mechanical Engineering. 28(6). 1254–1260. 12 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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