Yunpeng Liu

713 total citations · 1 hit paper
27 papers, 505 citations indexed

About

Yunpeng Liu is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Yunpeng Liu has authored 27 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Control and Systems Engineering, 12 papers in Mechanical Engineering and 6 papers in Mechanics of Materials. Recurrent topics in Yunpeng Liu's work include Machine Fault Diagnosis Techniques (18 papers), Fault Detection and Control Systems (9 papers) and Gear and Bearing Dynamics Analysis (9 papers). Yunpeng Liu is often cited by papers focused on Machine Fault Diagnosis Techniques (18 papers), Fault Detection and Control Systems (9 papers) and Gear and Bearing Dynamics Analysis (9 papers). Yunpeng Liu collaborates with scholars based in China. Yunpeng Liu's co-authors include Hongkai Jiang, Zhenghong Wu, Shaowei Liu, Renhe Yao, Qiao Yang, Yutong Dong, Chaoqiang Liu, Tao Zeng, Ke Zhu and Yanfeng Wang and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and Journal of Sound and Vibration.

In The Last Decade

Yunpeng Liu

24 papers receiving 487 citations

Hit Papers

Counterfactual-augmented few-shot contrastive learning fo... 2024 2026 2025 2024 10 20 30 40 50

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yunpeng Liu China 11 386 203 120 112 64 27 505
Zhenhui Zhan China 11 449 1.2× 272 1.3× 126 1.1× 85 0.8× 40 0.6× 14 566
Yutong Dong China 11 291 0.8× 145 0.7× 96 0.8× 78 0.7× 44 0.7× 19 403
Dengyun Sun China 11 542 1.4× 305 1.5× 186 1.6× 88 0.8× 47 0.7× 20 623
Lizhi Liu China 7 496 1.3× 295 1.5× 184 1.5× 92 0.8× 59 0.9× 13 656
Jianguo Miao China 13 281 0.7× 230 1.1× 118 1.0× 68 0.6× 62 1.0× 30 495
Qiuyu Song China 9 396 1.0× 208 1.0× 141 1.2× 78 0.7× 31 0.5× 20 480
Guoxi Sun China 6 472 1.2× 263 1.3× 155 1.3× 90 0.8× 47 0.7× 15 557
Yadong Lu United States 4 300 0.8× 152 0.7× 89 0.7× 50 0.4× 56 0.9× 8 385
Qiao Yang China 7 218 0.6× 125 0.6× 69 0.6× 67 0.6× 35 0.5× 24 329
Zhen Shi China 10 305 0.8× 170 0.8× 103 0.9× 68 0.6× 32 0.5× 24 401

Countries citing papers authored by Yunpeng Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yunpeng Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yunpeng Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Yunpeng Liu. A scholar is included among the top collaborators of Yunpeng Liu 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 Yunpeng Liu. Yunpeng Liu 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.
Jiang, Hongkai, et al.. (2025). AHWCN: An interpretable attention-guided hierarchical wavelet convolutional network for rotating machinery intelligent fault diagnosis. Expert Systems with Applications. 272. 126815–126815. 12 indexed citations
2.
Wang, Peng, Wenliang Wang, Jiaxuan Zhang, et al.. (2025). Rammed earth-inspired superhydrophobic monolith with superior wear resistance and self-regenerative recyclability. Applied Materials Today. 44. 102773–102773.
3.
Liu, Yunpeng, et al.. (2025). Micro-Arc oxidation-assisted silver coating for enhanced high-temperature wear resistance of TC4 alloy. Materials Letters. 402. 139370–139370. 1 indexed citations
4.
Yao, Renhe, et al.. (2024). Deep discriminative sparse representation learning for machinery fault diagnosis. Engineering Applications of Artificial Intelligence. 135. 108836–108836. 6 indexed citations
6.
Dong, Yutong, et al.. (2024). Global wavelet-integrated residual frequency attention regularized network for hypersonic flight vehicle fault diagnosis with imbalanced data. Engineering Applications of Artificial Intelligence. 132. 107968–107968. 28 indexed citations
7.
Wang, Xin, Hongkai Jiang, Yunpeng Liu, Shaowei Liu, & Qiao Yang. (2023). A dynamic spectrum loss generative adversarial network for intelligent fault diagnosis with imbalanced data. Engineering Applications of Artificial Intelligence. 126. 106872–106872. 14 indexed citations
8.
Dong, Yutong, Hongkai Jiang, Zhenghong Wu, Qiao Yang, & Yunpeng Liu. (2023). Digital twin-assisted multiscale residual-self-attention feature fusion network for hypersonic flight vehicle fault diagnosis. Reliability Engineering & System Safety. 235. 109253–109253. 68 indexed citations
9.
Wu, Zhenghong, et al.. (2023). Conditional distribution-guided adversarial transfer learning network with multi-source domains for rolling bearing fault diagnosis. Advanced Engineering Informatics. 56. 101993–101993. 39 indexed citations
10.
Jiang, Hongkai, et al.. (2023). A reinforcement double deep Q-network with prioritised experience replay for rolling bearing fault diagnosis. Measurement Science and Technology. 34(12). 125133–125133. 6 indexed citations
11.
Wang, Mengying, et al.. (2023). Emerging infectious disease surveillance using a hierarchical diagnosis model and the Knox algorithm. Scientific Reports. 13(1). 19836–19836. 4 indexed citations
12.
Yao, Renhe, et al.. (2023). An Integrated Framework via Spectrum Sparsity Measure and Dynamic Alarm Thresholds for Online Fault Detection. IEEE Sensors Journal. 23(24). 30642–30651. 1 indexed citations
13.
Wang, Ruixin, et al.. (2022). A Deep Ensemble Learning Model for Rolling Bearing Fault Diagnosis. 133–136. 3 indexed citations
14.
Liu, Yunpeng, et al.. (2022). Data-augmented wavelet capsule generative adversarial network for rolling bearing fault diagnosis. Knowledge-Based Systems. 252. 109439–109439. 77 indexed citations
15.
Yang, Shan, et al.. (2020). Root Cause Analysis of Failures for Power Communication Network Based on CNN. 100–105. 2 indexed citations
16.
Li, Gang, et al.. (2017). Large Power Transformer Fault Diagnosis and Prognostic Based on DBNC and D-S Evidence Theory. Energy and Power Engineering. 9(4). 232–239. 5 indexed citations
17.
Wang, Liang, Yunpeng Liu, & Xiangdong Liu. (2017). A novel global sliding mode control strategy for attitude control of reusable launch vehicles in the reentry phase. 68. 3615–3620. 2 indexed citations
18.
Wang, Xiaohui, et al.. (2016). Research and Implementation of Partial Discharge in HV Switchgear Using TEV Sensor. 52(10). 26.
19.
Liu, Yunpeng. (2012). Intelligent Terminal of Substation Equipment Condition Monitoring Based on UDP. Science Technology and Engineering. 1 indexed citations
20.
Liu, Yunpeng. (2004). STUDY OF THE MATHEMATICAL MORPHOLOGICAL FILTER IN SUPPRESSING PERIODIC NARROW BANDWIDTH NOISE OF PD. Proceedings of the Csee. 8 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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