Shuangwen Sheng

2.4k total citations
73 papers, 1.3k citations indexed

About

Shuangwen Sheng is a scholar working on Control and Systems Engineering, Mechanical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Shuangwen Sheng has authored 73 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Control and Systems Engineering, 36 papers in Mechanical Engineering and 15 papers in Electrical and Electronic Engineering. Recurrent topics in Shuangwen Sheng's work include Machine Fault Diagnosis Techniques (39 papers), Gear and Bearing Dynamics Analysis (27 papers) and Real-time simulation and control systems (12 papers). Shuangwen Sheng is often cited by papers focused on Machine Fault Diagnosis Techniques (39 papers), Gear and Bearing Dynamics Analysis (27 papers) and Real-time simulation and control systems (12 papers). Shuangwen Sheng collaborates with scholars based in United States, China and Belgium. Shuangwen Sheng's co-authors include Jonathan Keller, Ali Erdemir, Aaron Greco, Jaspreet Singh Dhupia, Liu Hong, Zhiwei Gao, Donatella Zappalá, Christopher Crabtree, Paul Fleming and Caleb Phillips and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Applied Energy and Renewable Energy.

In The Last Decade

Shuangwen Sheng

69 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuangwen Sheng United States 19 797 624 283 240 201 73 1.3k
Eric Bechhoefer United States 22 1.3k 1.6× 920 1.5× 333 1.2× 144 0.6× 263 1.3× 98 1.7k
Yongqiang Liu China 20 796 1.0× 929 1.5× 332 1.2× 94 0.4× 158 0.8× 101 1.4k
Chul Ki Song South Korea 10 663 0.8× 359 0.6× 131 0.5× 185 0.8× 351 1.7× 31 1.0k
Wenyi Wang Australia 17 760 1.0× 676 1.1× 205 0.7× 99 0.4× 216 1.1× 65 1.3k
Mileta Tomovic United States 18 482 0.6× 528 0.8× 179 0.6× 113 0.5× 43 0.2× 83 1.1k
Guangfu Bin China 17 637 0.8× 588 0.9× 292 1.0× 111 0.5× 126 0.6× 62 1.1k
Zhi Zhai China 18 476 0.6× 395 0.6× 421 1.5× 389 1.6× 163 0.8× 80 1.4k
Jan Helsen Belgium 17 804 1.0× 730 1.2× 231 0.8× 188 0.8× 279 1.4× 113 1.3k
Zhinong Jiang China 22 1.1k 1.4× 819 1.3× 430 1.5× 113 0.5× 190 0.9× 78 1.5k
Guy Clerc France 20 1.1k 1.4× 509 0.8× 256 0.9× 545 2.3× 84 0.4× 71 1.6k

Countries citing papers authored by Shuangwen Sheng

Since Specialization
Citations

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

Fields of papers citing papers by Shuangwen Sheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuangwen Sheng

This figure shows the co-authorship network connecting the top 25 collaborators of Shuangwen Sheng. A scholar is included among the top collaborators of Shuangwen Sheng 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 Shuangwen Sheng. Shuangwen Sheng 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.
Barber, Sarah, et al.. (2023). A use-case-driven approach for demonstrating the added value of digitalisation in wind energy. Journal of Physics Conference Series. 2507(1). 12002–12002. 1 indexed citations
2.
3.
Verma, Ayush, Donatella Zappalá, Shuangwen Sheng, & Simon Watson. (2022). Wind turbine gearbox fault prognosis using high-frequency SCADA data. Journal of Physics Conference Series. 2265(3). 32067–32067. 8 indexed citations
4.
Optis, Mike, Jason Fields, Nicola Bodini, et al.. (2021). OpenOA: An Open-Source Codebase For Operational Analysis of Wind Farms. The Journal of Open Source Software. 6(58). 2171–2171. 8 indexed citations
5.
Guo, Yi, et al.. (2020). Prognosis of Wind Turbine Gearbox Bearing Failures using SCADA and Modeled Data. Annual Conference of the PHM Society. 12(1). 10–10. 11 indexed citations
6.
Guo, Yi, et al.. (2020). A methodology for reliability assessment and prognosis of bearing axial cracking in wind turbine gearboxes. Renewable and Sustainable Energy Reviews. 127. 109888–109888. 43 indexed citations
7.
Guo, Yi, et al.. (2020). Gaining Insights in Loading Events for Wind Turbine Drivetrain Prognostics. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 3 indexed citations
8.
Optis, Mike, Joseph Lee, Travis Kemper, et al.. (2019). OpenOA: An Open-Source Code Base for Operational Analysis of Wind Power Plants. 4 indexed citations
9.
Mauricio, Alexandre, Shuangwen Sheng, & Konstantinos Gryllias. (2019). Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions. Journal of Engineering for Gas Turbines and Power. 142(3). 15 indexed citations
10.
Faulstich, Stefan, et al.. (2019). Recommended key performance indicators for operational management of wind turbines. Journal of Physics Conference Series. 1356(1). 12040–12040. 13 indexed citations
11.
Sheng, Shuangwen, et al.. (2017). Wind Turbine Drivetrain Condition Monitoring - An Overview (Presentation). OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 7 indexed citations
12.
Ren, Zhengwei, et al.. (2017). Distributed contingency analysis over wide area network among dispatch centers. 1–5. 1 indexed citations
13.
Sheng, Shuangwen. (2017). Gearbox Typical Failure Modes, Detection, and Mitigation Methods (Presentation). OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 3 indexed citations
14.
Sheng, Shuangwen. (2014). Gearbox Typical Failure Modes, Detection, and Mitigation Methods. University of North Texas Digital Library (University of North Texas). 6 indexed citations
15.
Sheng, Shuangwen. (2011). Investigation of Various Wind Turbine Drivetrain Condition Monitoring Techniques (Presentation). OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 82. 6043–52. 1 indexed citations
16.
Sheng, Shuangwen. (2011). Investigation of Various Condition Monitoring Techniques Based on a Damaged Wind Turbine Gearbox. Structural Health Monitoring. 18 indexed citations
17.
Kim, Kyusung, et al.. (2011). Use of SCADA Data for Failure Detection in Wind Turbines. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2071–2079. 113 indexed citations
18.
Sheng, Shuangwen, F. Oyague, & S. Butterfield. (2010). Investigation of Various Wind Turbine Drivetrain Condition Monitoring Techniques. University of North Texas Digital Library (University of North Texas). 8 indexed citations
19.
Sheng, Shuangwen & Robert X. Gao. (2006). Optimization of ANFIS with Applications in Machine Defect Severity Classification. The 2006 IEEE International Joint Conference on Neural Network Proceedings. 21. 728–734. 2 indexed citations
20.
Sheng, Shuangwen, et al.. (2006). A Systematic Sensor-Placement Strategy for Enhanced Defect Detection in Rolling Bearings. IEEE Sensors Journal. 6(5). 1346–1354. 19 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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