Jing Yuan

1.7k total citations · 1 hit paper
55 papers, 1.4k citations indexed

About

Jing Yuan is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Jing Yuan has authored 55 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Control and Systems Engineering, 14 papers in Mechanical Engineering and 11 papers in Mechanics of Materials. Recurrent topics in Jing Yuan's work include Machine Fault Diagnosis Techniques (35 papers), Fault Detection and Control Systems (17 papers) and Gear and Bearing Dynamics Analysis (11 papers). Jing Yuan is often cited by papers focused on Machine Fault Diagnosis Techniques (35 papers), Fault Detection and Control Systems (17 papers) and Gear and Bearing Dynamics Analysis (11 papers). Jing Yuan collaborates with scholars based in China, United States and Canada. Jing Yuan's co-authors include Yanyang Zi, Zhengjia He, Jinglong Chen, Jun Pan, Zipeng Li, Binqiang Chen, Qian Zhao, Huiming Jiang, Hailiang Sun and Xiaodong Wang and has published in prestigious journals such as Energy Conversion and Management, IEEE Access and Sensors.

In The Last Decade

Jing Yuan

48 papers receiving 1.3k citations

Hit Papers

Wavelet transform based o... 2015 2026 2018 2022 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jing Yuan China 20 1.0k 671 384 204 166 55 1.4k
Xuejun Li China 21 801 0.8× 773 1.2× 384 1.0× 229 1.1× 152 0.9× 134 1.5k
Zhinong Jiang China 22 1.1k 1.1× 819 1.2× 430 1.1× 190 0.9× 113 0.7× 78 1.5k
Yanhe Xu China 19 1.0k 1.0× 557 0.8× 474 1.2× 299 1.5× 494 3.0× 43 1.6k
Jianzhong Zhou China 15 1.0k 1.0× 674 1.0× 425 1.1× 136 0.7× 211 1.3× 28 1.3k
Jun Pan China 12 1.4k 1.4× 937 1.4× 494 1.3× 237 1.2× 160 1.0× 30 1.7k
Feiyun Cong China 15 516 0.5× 411 0.6× 196 0.5× 98 0.5× 86 0.5× 52 805
Yang Zheng China 21 1.1k 1.1× 504 0.8× 455 1.2× 252 1.2× 706 4.3× 74 1.8k
Lotfi Saïdi Tunisia 18 1.9k 1.8× 1.2k 1.9× 600 1.6× 227 1.1× 282 1.7× 58 2.4k
Xuezhi Zhao China 16 442 0.4× 439 0.7× 239 0.6× 164 0.8× 109 0.7× 63 898

Countries citing papers authored by Jing Yuan

Since Specialization
Citations

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

Fields of papers citing papers by Jing Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jing Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Yuan. A scholar is included among the top collaborators of Jing Yuan 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 Jing Yuan. Jing Yuan 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.
Bai, Hongwei, et al.. (2025). AI detection of poor contact faults in optical fiber jumper joints based on Elman neural network. Optics Communications. 600. 132692–132692.
2.
Yuan, Jing, et al.. (2025). Interpretable adaptive multiwavelet kernel-driven two-dimensional convolutional neural network for mechanical fault diagnosis. Engineering Applications of Artificial Intelligence. 159. 111614–111614.
3.
Yuan, Jing, et al.. (2025). A Novel Dynamic Health Index Based on Core Graph Model of Multichannel Signals for Machine Health Monitoring. IEEE Transactions on Instrumentation and Measurement. 74. 1–13.
4.
Yuan, Jing, et al.. (2025). Endogenous Noise-Expanded Multivariate Empirical Mode Decomposition and Its Application to Mechanical Compound Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement. 74. 1–11. 1 indexed citations
5.
Yuan, Jing, et al.. (2024). A novel weighted sparsity index based on multichannel fused graph spectra for machine health monitoring. Mechanical Systems and Signal Processing. 215. 111417–111417. 8 indexed citations
6.
Yuan, Jing, et al.. (2023). Tensor Denoising Assisted Time-Reassigned Synchrosqueezing Wavelet Transform for Gear Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement. 72. 1–12. 10 indexed citations
7.
Yuan, Jing, et al.. (2022). High-fidelity noise-reconstructed empirical mode decomposition for mechanical multiple and weak fault extractions. ISA Transactions. 129(Pt B). 380–397. 23 indexed citations
8.
Yuan, Jing, et al.. (2022). Multi-lifting synchrosqueezing transform for nonstationary signal analysis of rotating machinery. Measurement. 191. 110758–110758. 13 indexed citations
9.
Yuan, Jing, et al.. (2021). Dual-Core Denoised Synchrosqueezing Wavelet Transform for Gear Fault Detection. IEEE Transactions on Instrumentation and Measurement. 70. 1–11. 19 indexed citations
10.
Zhao, Qian, Jing Yuan, Huiming Jiang, Hongliang Yao, & Bangchun Wen. (2020). Vibration control of a rotor system by shear thickening fluid dampers. Journal of Sound and Vibration. 494. 115883–115883. 40 indexed citations
11.
Jiang, Huiming, et al.. (2020). A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute Projection. IEEE Access. 8. 49629–49644. 7 indexed citations
12.
Yuan, Jing, et al.. (2018). Development and evaluation of Preschooler′s Parents Feeding Behavior Scale. Chinese Journal of Child Health Care. 26(5). 483. 2 indexed citations
13.
Yuan, Jing, et al.. (2015). A Comparative Study on Multiwavelet Construction Methods and Customized Multiwavelet Library for Mechanical Fault Detection. Shock and Vibration. 2015. 1–12. 12 indexed citations
14.
Yuan, Jing, et al.. (2013). Ensemble Noise-Reconstructed Empirical Mode Decomposition for Mechanical Fault Detection. Journal of vibration and acoustics. 135(2). 25 indexed citations
15.
Chen, Jinglong, Yanyang Zi, Zhengjia He, & Jing Yuan. (2012). Improved spectral kurtosis with adaptive redundant multiwavelet packet and its applications for rotating machinery fault detection. Measurement Science and Technology. 23(4). 45608–45608. 34 indexed citations
16.
Chen, Jinglong, Yanyang Zi, Zhengjia He, & Jing Yuan. (2012). Compound faults detection of rotating machinery using improved adaptive redundant lifting multiwavelet. Mechanical Systems and Signal Processing. 38(1). 36–54. 69 indexed citations
17.
Sun, Hailiang, Yanyang Zi, HE Zheng-jia, Xiaodong Wang, & Jing Yuan. (2011). Translation-invariant multiwavelet denoising using improved neighbouring coefficients and its application on rolling bearing fault diagnosis. Journal of Physics Conference Series. 305. 12012–12012. 6 indexed citations
18.
Chen, Jiaxi, et al.. (2011). Reliability Analysis of System-in-the-Loop Network Platform Based on Delays. 750–753. 1 indexed citations
19.
Yuan, Jing, et al.. (2009). Research on reliability modeling of complex system based on dynamic fault tree. 137–137. 2 indexed citations
20.
Yuan, Jing. (2006). Method and Application of Reliability Simulation Using Improved Fault Tree Analysis. Jisuanji yingyong yanjiu. 2 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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