Sheng Shan

1.3k total citations · 1 hit paper
43 papers, 919 citations indexed

About

Sheng Shan is a scholar working on Mechanical Engineering, Control and Systems Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Sheng Shan has authored 43 papers receiving a total of 919 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Mechanical Engineering, 15 papers in Control and Systems Engineering and 12 papers in Industrial and Manufacturing Engineering. Recurrent topics in Sheng Shan's work include Machine Fault Diagnosis Techniques (15 papers), Gear and Bearing Dynamics Analysis (13 papers) and Railway Systems and Energy Efficiency (7 papers). Sheng Shan is often cited by papers focused on Machine Fault Diagnosis Techniques (15 papers), Gear and Bearing Dynamics Analysis (13 papers) and Railway Systems and Energy Efficiency (7 papers). Sheng Shan collaborates with scholars based in China, United States and Austria. Sheng Shan's co-authors include Deqiang He, Zhenzhen Jin, Yanjun Chen, Yanjun Chen, Jian Miao, Rui Ma, Larry J. Brant, Chenyu Liu, Zhenpeng Lao and Luigi Ferrucci and has published in prestigious journals such as Blood, Journal of Cleaner Production and Applied Energy.

In The Last Decade

Sheng Shan

39 papers receiving 895 citations

Hit Papers

Temporal multi-resolution hypergraph attention network fo... 2024 2026 2025 2024 20 40 60

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sheng Shan China 16 355 301 144 120 98 43 919
K. Mathioudakis Greece 28 875 2.5× 549 1.8× 44 0.3× 387 3.2× 166 1.7× 181 2.5k
Félix Schmid United Kingdom 22 221 0.6× 574 1.9× 458 3.2× 83 0.7× 104 1.1× 86 1.6k
Dawei Gao China 15 369 1.0× 269 0.9× 42 0.3× 118 1.0× 143 1.5× 35 857
Ye Zhang China 21 228 0.6× 188 0.6× 133 0.9× 44 0.4× 164 1.7× 104 1.4k
Wu Deng China 22 454 1.3× 248 0.8× 114 0.8× 138 1.1× 348 3.6× 57 1.3k
Hengchang Liu China 10 282 0.8× 204 0.7× 39 0.3× 92 0.8× 59 0.6× 26 559
Zhenzhen Jin China 17 772 2.2× 505 1.7× 97 0.7× 261 2.2× 119 1.2× 53 1.1k
Mihaela Mitici Netherlands 19 385 1.1× 79 0.3× 91 0.6× 73 0.6× 58 0.6× 47 1.1k
Wenbing Chang China 16 156 0.4× 65 0.2× 20 0.1× 40 0.3× 163 1.7× 50 747
Huawei Wang China 17 653 1.8× 354 1.2× 178 1.2× 224 1.9× 132 1.3× 67 1.1k

Countries citing papers authored by Sheng Shan

Since Specialization
Citations

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

Fields of papers citing papers by Sheng Shan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng Shan

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng Shan. A scholar is included among the top collaborators of Sheng Shan 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 Sheng Shan. Sheng Shan 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.
He, Deqiang, et al.. (2024). Welding defect detection based on phased array images and two-stage segmentation strategy. Advanced Engineering Informatics. 62. 102879–102879. 7 indexed citations
2.
He, Deqiang, et al.. (2024). A train bearing imbalanced fault diagnosis method based on extended CCR and multi-scale feature fusion network. Nonlinear Dynamics. 112(15). 13147–13173. 12 indexed citations
3.
He, Deqiang, Zhenzhen Jin, Jian Miao, et al.. (2024). ViTR-Net: An unsupervised lightweight transformer network for cable surface defect detection and adaptive classification. Engineering Structures. 313. 118240–118240. 8 indexed citations
4.
Zhong, Hao, Deqiang He, Zexian Wei, et al.. (2024). A novel meta-learning network with adversarial domain-adaptation and attention mechanism for cross-domain for train bearing fault diagnosis. Measurement Science and Technology. 35(12). 125109–125109. 6 indexed citations
5.
Chen, Qilin, et al.. (2024). MSRNet-GLAM: A novel intrusion detection method for train communication network. Simulation Modelling Practice and Theory. 138. 103040–103040. 2 indexed citations
7.
He, Deqiang, et al.. (2023). Remaining useful life prediction for train bearing based on an ILSTM network with adaptive hyperparameter optimization. Transportation Safety and Environment. 6(2). 3 indexed citations
8.
He, Deqiang, et al.. (2023). Research on flow scheduling of train communication based on time-sensitive network. Simulation Modelling Practice and Theory. 130. 102859–102859. 5 indexed citations
9.
He, Deqiang, et al.. (2023). Personalized fault diagnosis of rolling bearings in trains based on digital twin. Measurement Science and Technology. 34(12). 125131–125131. 6 indexed citations
10.
Sun, Zheng, et al.. (2023). A bi-objective optimization model of metro trains considering energy conservation and passenger waiting time. Journal of Cleaner Production. 437. 140427–140427. 5 indexed citations
11.
He, Deqiang, et al.. (2023). Preventive maintenance optimization for key components of subway train bogie with consideration of failure risk. Engineering Failure Analysis. 154. 107634–107634. 56 indexed citations
12.
He, Deqiang, et al.. (2023). A multi-layer feature fusion fault diagnosis method for train bearings under noise and variable load working conditions. Measurement Science and Technology. 35(2). 25121–25121. 3 indexed citations
13.
Wei, Zexian, Deqiang He, Zhenzhen Jin, et al.. (2023). Intelligent fault diagnosis and health stage division of bearing based on tensor clustering and feature space denoising. Applied Intelligence. 53(21). 24671–24688. 8 indexed citations
14.
He, Deqiang, et al.. (2021). Obstacle detection in dangerous railway track areas by a convolutional neural network. Measurement Science and Technology. 32(10). 105401–105401. 23 indexed citations
15.
He, Deqiang, Chenyu Liu, Yanjun Chen, et al.. (2021). A rolling bearing fault diagnosis method using novel lightweight neural network. Measurement Science and Technology. 32(12). 125102–125102. 28 indexed citations
16.
Morrell, Christopher H., Larry J. Brant, Sheng Shan, & E. Jeffrey Metter. (2012). Screening for prostate cancer using multivariate mixed-effects models. Journal of Applied Statistics. 39(6). 1151–1175. 17 indexed citations
17.
Morrell, Christopher H., Sheng Shan, & Larry J. Brant. (2011). A Comparative Study of Approaches for Predicting Prostate Cancer from Longitudinal Data. Communications in Statistics - Simulation and Computation. 40(9). 1494–1513. 5 indexed citations
18.
Brant, Larry J., Luigi Ferrucci, Sheng Shan, et al.. (2010). Gender differences in the accuracy of time-dependent blood pressure indices for predicting coronary heart disease: A random-effects modeling approach. Gender Medicine. 7(6). 616–627. 7 indexed citations
19.
Croteau, Deborah L., Nadja C. de Souza‐Pinto, Guido Keijzers, et al.. (2010). DNA Repair and the Accumulation of Oxidatively Damaged DNA Are Affected by Fruit Intake in Mice. The Journals of Gerontology Series A. 65A(12). 1300–1311. 7 indexed citations
20.
Ershler, William B., Sheng Shan, Andrew Artz, et al.. (2005). Serum Erythropoietin and Aging: A Longitudinal Analysis. Journal of the American Geriatrics Society. 53(8). 1360–1365. 121 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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