Xing Wu

2.9k total citations · 1 hit paper
100 papers, 2.2k citations indexed

About

Xing Wu is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Xing Wu has authored 100 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Control and Systems Engineering, 44 papers in Mechanical Engineering and 15 papers in Mechanics of Materials. Recurrent topics in Xing Wu's work include Machine Fault Diagnosis Techniques (25 papers), Gear and Bearing Dynamics Analysis (19 papers) and Fault Detection and Control Systems (13 papers). Xing Wu is often cited by papers focused on Machine Fault Diagnosis Techniques (25 papers), Gear and Bearing Dynamics Analysis (19 papers) and Fault Detection and Control Systems (13 papers). Xing Wu collaborates with scholars based in China, United Kingdom and Taiwan. Xing Wu's co-authors include Jing Na, Yingbo Huang, Yu Guo, Tao Liu, Guanbin Gao, Hua Li, Qing Chen, Xiaoqin Liu, Guang Li and Juan Yang and has published in prestigious journals such as Applied Physics Letters, IEEE Transactions on Industrial Electronics and Automatica.

In The Last Decade

Xing Wu

91 papers receiving 2.2k citations

Hit Papers

An optimized VMD method and its applications in bearing f... 2020 2026 2022 2024 2020 50 100 150 200 250
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. An optimized VMD method and its applications in bearing fault diagnosis
    2020 273 citations Hua Li, Tao Liu 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
Xing Wu China 21 1.4k 951 558 372 237 100 2.2k
Yu Guo China 28 1.7k 1.3× 1.3k 1.4× 533 1.0× 242 0.7× 223 0.9× 144 2.7k
Arun Kumar Samantaray India 28 1.5k 1.1× 1.1k 1.2× 271 0.5× 194 0.5× 268 1.1× 112 2.5k
Z. Mohamed Malaysia 30 2.6k 2.0× 1.1k 1.1× 299 0.5× 631 1.7× 103 0.4× 151 3.1k
Gary Balas United States 39 3.6k 2.7× 410 0.4× 416 0.7× 411 1.1× 228 1.0× 173 4.8k
Magnus Gäfvert Sweden 16 1.3k 0.9× 955 1.0× 235 0.4× 426 1.1× 119 0.5× 47 2.0k
Wenxiang Deng China 24 2.4k 1.8× 1.8k 1.9× 145 0.3× 194 0.5× 215 0.9× 84 3.1k
Mien Van United Kingdom 29 2.3k 1.7× 708 0.7× 134 0.2× 132 0.4× 185 0.8× 72 2.9k
Domenico Guida Italy 25 708 0.5× 622 0.7× 377 0.7× 400 1.1× 79 0.3× 99 1.4k
Qiang Chen China 29 2.6k 1.9× 698 0.7× 111 0.2× 176 0.5× 442 1.9× 147 3.2k
Ahmed El Hajjaji France 26 2.0k 1.5× 292 0.3× 189 0.3× 638 1.7× 540 2.3× 221 2.8k

Countries citing papers authored by Xing Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xing Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xing Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Xing Wu. A scholar is included among the top collaborators of Xing Wu 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 Xing Wu. Xing Wu 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.
Wu, Xing, et al.. (2025). Vision-based non-contact vibration measurement and fault diagnosis of rolling bearings. Measurement Science and Technology. 37(2). 26002–26002.
2.
Liu, Chang, et al.. (2025). A Fault Diagnosis Method for Variable Condition Equipment Based on Knowledge Transfer and Improved Residual Neural Networks. IEEE Transactions on Instrumentation and Measurement. 74. 1–16. 2 indexed citations
3.
Wu, Xing, et al.. (2025). Bearing defect localization based on multiple arrivals detection via matching pursuit using single AE sensor. Mechanical Systems and Signal Processing. 230. 112671–112671.
4.
Wu, Xing, et al.. (2024). ERP evidence for cross-domain prosodic priming from music to speech. Brain and Language. 254. 105439–105439.
5.
Liu, Tao, et al.. (2024). A Rolling Bearing Performance Degradation Evaluation Method Based on Statistical Correlation Superposition. IEEE Transactions on Instrumentation and Measurement. 73. 1–11. 2 indexed citations
6.
Liu, Tao, et al.. (2024). A Fault Diagnosis Method Based on NTFES-FCCT for Variable Working Condition Bearing Signals. IEEE Sensors Journal. 24(13). 20989–20998. 7 indexed citations
7.
Li, Hua, Xing Wu, Tao Liu, & Shaobo Li. (2023). Rotating Machinery Fault Diagnosis Based on Typical Resonance Demodulation Methods: A Review. IEEE Sensors Journal. 23(7). 6439–6459. 36 indexed citations
8.
Liu, Tao, et al.. (2023). Characteristic enhancement of RV reducer under non-stationary condition based on WDT-IF-SS-VMD. Measurement Science and Technology. 34(10). 105108–105108. 2 indexed citations
9.
Liu, Tao, et al.. (2023). Application of an Oversampling Method Based on GMM and Boundary Optimization in Imbalance-Bearing Fault Diagnosis. IEEE Transactions on Industrial Informatics. 20(2). 1931–1940. 33 indexed citations
10.
Wu, Xing, et al.. (2023). Application of Mutual Information Maximization Convolutional Neural Network in Bearing Feature Extraction. IEEE Sensors Journal. 23(24). 30584–30592. 3 indexed citations
11.
Liu, Tao, et al.. (2023). Research on bearing vibration signal generation method based on filtering WGAN_GP with small samples. Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science. 237(20). 4911–4929. 6 indexed citations
12.
Li, Hua, Xing Wu, Tao Liu, & Shaobo Li. (2022). The Methodology of Modified Frequency Band Envelope Kurtosis for Bearing Fault Diagnosis. IEEE Transactions on Industrial Informatics. 19(3). 2856–2865. 19 indexed citations
13.
Li, Hua, Tao Liu, Xing Wu, & Shaobo Li. (2021). Correlated SVD and Its Application in Bearing Fault Diagnosis. IEEE Transactions on Neural Networks and Learning Systems. 34(1). 355–365. 38 indexed citations
14.
Li, Hua, Tao Liu, Xing Wu, & Qing Chen. (2020). A Bearing Fault Diagnosis Method Based on Enhanced Singular Value Decomposition. IEEE Transactions on Industrial Informatics. 17(5). 3220–3230. 110 indexed citations
15.
Liu, Xiaoqin, et al.. (2020). Three-Dimensional Sound Field Reconstruction and Sound Power Estimation by Stereo Vision and Beamforming Technology. Applied Sciences. 11(1). 92–92. 2 indexed citations
16.
17.
Na, Jing, Yingbo Huang, Xing Wu, Shun‐Feng Su, & Guang Li. (2019). Adaptive Finite-Time Fuzzy Control of Nonlinear Active Suspension Systems With Input Delay. IEEE Transactions on Cybernetics. 50(6). 2639–2650. 189 indexed citations
18.
Jiao, Zaibin, et al.. (2016). Research of New Scheme of Adaptive Overvoltage Protection in Hybrid AC/DC Grid. Power System Technology. 40(8). 2541–2547.
19.
Wu, Xing. (2009). Intelligent Predictive Control Based on State Analysis of Visual Field for Robot Path Tracking. Robot. 1 indexed citations
20.
Wu, Xing. (2001). Study on Starting Characteristics of Switched Reluctance Motor. 1 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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