Kun Feng

925 total citations · 1 hit paper
31 papers, 758 citations indexed

About

Kun Feng is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Kun Feng has authored 31 papers receiving a total of 758 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Control and Systems Engineering, 15 papers in Mechanical Engineering and 12 papers in Mechanics of Materials. Recurrent topics in Kun Feng's work include Machine Fault Diagnosis Techniques (18 papers), Fault Detection and Control Systems (11 papers) and Engineering Diagnostics and Reliability (9 papers). Kun Feng is often cited by papers focused on Machine Fault Diagnosis Techniques (18 papers), Fault Detection and Control Systems (11 papers) and Engineering Diagnostics and Reliability (9 papers). Kun Feng collaborates with scholars based in China, Japan and United States. Kun Feng's co-authors include Zhinong Jiang, Ming Zhang, Wei He, Qiang Qin, Wei Sun, Ahmet Palazoğlu, Qiong Chen, Juntai Shi, Xianyue Xiong and Cheng Liu and has published in prestigious journals such as IEEE Access, Sensors and Journal of Sound and Vibration.

In The Last Decade

Kun Feng

27 papers receiving 736 citations

Hit Papers

Research on variational mode decomposition in rolling bea... 2017 2026 2020 2023 2017 100 200 300
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. Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump
    2017 333 citations Zhinong Jiang, Kun Feng et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kun Feng China 10 595 480 244 108 61 31 758
Hongchao Wang China 10 482 0.8× 337 0.7× 186 0.8× 73 0.7× 30 0.5× 59 631
Jiande Wu China 13 419 0.7× 306 0.6× 136 0.6× 74 0.7× 39 0.6× 90 604
Zhongjie Shen China 11 620 1.0× 445 0.9× 263 1.1× 83 0.8× 17 0.3× 17 766
Zuoyi Chen China 13 341 0.6× 265 0.6× 156 0.6× 80 0.7× 30 0.5× 36 574
Shanshan Ji China 10 469 0.8× 292 0.6× 146 0.6× 42 0.4× 49 0.8× 20 640
Yi Zang China 5 485 0.8× 291 0.6× 162 0.7× 45 0.4× 23 0.4× 9 562
Yuhe Liao China 14 377 0.6× 294 0.6× 112 0.5× 85 0.8× 17 0.3× 40 566
Rujiang Hao China 16 543 0.9× 418 0.9× 166 0.7× 108 1.0× 16 0.3× 44 659
Yilun Liu China 12 280 0.5× 274 0.6× 161 0.7× 94 0.9× 16 0.3× 37 514

Countries citing papers authored by Kun Feng

Since Specialization
Citations

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

Fields of papers citing papers by Kun Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Kun Feng. A scholar is included among the top collaborators of Kun Feng 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 Kun Feng. Kun Feng 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.
Feng, Kun, et al.. (2025). Integrating Casing Vibration and Reconstructed Pressure Signal for Gas Turbine Blade Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement. 74. 1–11. 1 indexed citations
2.
Zhang, Jingxuan, et al.. (2025). Sparse Bayesian PC-Kriging modeling with multi-criteria active learning for structural reliability: Application to shield tunnel structures. Tunnelling and Underground Space Technology. 166. 106961–106961.
3.
4.
Feng, Kun, et al.. (2024). A fusion autoencoder model and piecewise anomaly index for aero-engine fault diagnosis. Applied Intelligence. 54(20). 10148–10160. 1 indexed citations
5.
Jin, Li, et al.. (2023). A 3-D finite element modeling method for time-varying rotor-support system based on rotating-fixed coordinates. Journal of Sound and Vibration. 568. 117977–117977. 4 indexed citations
6.
Feng, Kun, et al.. (2023). Operational data-based adaptive improvement method of gas turbine component characteristics for performance simulation. Journal of Mechanical Science and Technology. 37(12). 6691–6709. 2 indexed citations
7.
8.
Feng, Kun, et al.. (2022). Determining Dynamic Thresholds for Gas Turbine Engine Condition Monitoring. IEEE Access. 10. 87404–87414. 4 indexed citations
9.
Yang, Liping, et al.. (2021). Evaluation Method of Rotating Machinery Health State Based on TPE-XGBoost. 24. 1–6. 2 indexed citations
10.
Feng, Kun, et al.. (2021). Simulation Analysis Method for Equivalent Mechanical Characteristics of Rotor Asymmetric Supports with Bearing Clearance. Journal of Mechanical Engineering. 57(19). 138–138. 1 indexed citations
11.
Feng, Kun, et al.. (2020). An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds. Shock and Vibration. 2020. 1–21. 4 indexed citations
12.
13.
Jiang, Zhinong, et al.. (2020). A double integral method for quantitative evaluation of influence on thin-walled casing response caused by bearing uncertainties. Chinese Journal of Aeronautics. 33(9). 2372–2381. 7 indexed citations
14.
Feng, Kun, et al.. (2020). An Intelligent Fault Diagnosis Scheme Using Transferred Samples for Intershaft Bearings Under Variable Working Conditions. IEEE Access. 8. 203058–203069. 11 indexed citations
15.
Liu, Sijin, Chuan He, Qi Sun, & Kun Feng. (2017). Safety Guarantee Measures for Subsea Shield Tunnel Segments Based on Life Cycle Deterioration Analysis. Strategic Study of CAE. 19(6). 52–52. 2 indexed citations
16.
Qin, Qiang, Zhinong Jiang, Kun Feng, & Wei He. (2012). A novel scheme for fault detection of reciprocating compressor valves based on basis pursuit, wave matching and support vector machine. Measurement. 45(5). 897–908. 54 indexed citations
17.
Sun, Wei, et al.. (2012). Fault diagnosis of rolling bearing based on wavelet transform and envelope spectrum correlation. Journal of Vibration and Control. 19(6). 924–941. 72 indexed citations
18.
Feng, Kun. (2011). Adaptive Filtering Algorithm in Fault Diagnosis of Rolling Bearings. Bearing Jurnal Penelitian dan Kajian Teknik Sipil. 1 indexed citations
19.
Feng, Kun, Zhinong Jiang, Wei He, & Qiang Qin. (2011). Rolling element bearing fault detection based on optimal antisymmetric real Laplace wavelet. Measurement. 44(9). 1582–1591. 65 indexed citations
20.
He, Wei, Zhinong Jiang, & Kun Feng. (2009). Bearing fault detection based on optimal wavelet filter and sparse code shrinkage. Measurement. 42(7). 1092–1102. 103 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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