Shunming Li

4.2k total citations · 1 hit paper
186 papers, 3.5k citations indexed

About

Shunming Li is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Shunming Li has authored 186 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 116 papers in Control and Systems Engineering, 68 papers in Mechanical Engineering and 57 papers in Mechanics of Materials. Recurrent topics in Shunming Li's work include Machine Fault Diagnosis Techniques (103 papers), Gear and Bearing Dynamics Analysis (50 papers) and Fault Detection and Control Systems (45 papers). Shunming Li is often cited by papers focused on Machine Fault Diagnosis Techniques (103 papers), Gear and Bearing Dynamics Analysis (50 papers) and Fault Detection and Control Systems (45 papers). Shunming Li collaborates with scholars based in China, Singapore and United Kingdom. Shunming Li's co-authors include Jinrui Wang, Xingxing Jiang, Zenghui An, Weiwei Qian, Yu Xin, Jiantao Lu, Chun Cheng, Yong Wang, Zongzhen Zhang and Kun Xu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied and Environmental Microbiology and IEEE Access.

In The Last Decade

Shunming Li

169 papers receiving 3.4k citations

Hit Papers

Batch-normalized deep neural networks for achieving fast ... 2018 2026 2020 2023 2018 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shunming Li China 32 2.4k 1.6k 930 551 408 186 3.5k
Shibin Wang China 36 3.5k 1.4× 2.1k 1.3× 1.2k 1.3× 1.1k 1.9× 591 1.4× 177 5.2k
Diyi Chen China 40 1.7k 0.7× 953 0.6× 1.2k 1.3× 845 1.5× 309 0.8× 233 5.1k
Yixiang Huang China 27 887 0.4× 598 0.4× 273 0.3× 197 0.4× 247 0.6× 97 2.6k
Rajesh Kumar India 32 1.3k 0.5× 1.3k 0.8× 548 0.6× 272 0.5× 253 0.6× 103 2.7k
Zi–Qiang Lang United Kingdom 38 2.2k 0.9× 1.2k 0.8× 646 0.7× 2.6k 4.7× 159 0.4× 192 4.4k
Shaopu Yang China 34 1.6k 0.7× 1.8k 1.1× 696 0.7× 1.6k 2.9× 94 0.2× 202 4.0k
Hee‐Jun Kang South Korea 32 3.2k 1.3× 1.6k 1.0× 519 0.6× 138 0.3× 363 0.9× 133 3.9k
Mohammed Chadli France 55 6.8k 2.8× 783 0.5× 203 0.2× 469 0.9× 1.1k 2.8× 305 8.7k
Haijun Peng China 31 1.1k 0.5× 691 0.4× 198 0.2× 605 1.1× 107 0.3× 175 2.8k
Yueying Wang China 34 3.0k 1.2× 475 0.3× 207 0.2× 140 0.3× 381 0.9× 172 4.4k

Countries citing papers authored by Shunming Li

Since Specialization
Citations

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

Fields of papers citing papers by Shunming Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shunming Li

This figure shows the co-authorship network connecting the top 25 collaborators of Shunming Li. A scholar is included among the top collaborators of Shunming Li 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 Shunming Li. Shunming Li 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.
Lu, Jiantao, et al.. (2024). A modified active learning intelligent fault diagnosis method for rolling bearings with unbalanced samples. Advanced Engineering Informatics. 60. 102397–102397. 31 indexed citations
2.
Lu, Jiantao, et al.. (2023). A noise reduction method of rolling bearing based on empirical wavelet transform and adaptive time frequency peak filtering. Measurement Science and Technology. 34(12). 125146–125146. 15 indexed citations
3.
Lu, Jiantao, et al.. (2023). An Improved Underdetermined Blind Source Separation Method for Insufficiently Sparse Sources. Circuits Systems and Signal Processing. 42(12). 7615–7639. 3 indexed citations
4.
Li, Shunming, Jiantao Lu, Kun Xu, et al.. (2022). A Hierarchical Sparse Discriminant Autoencoder for Bearing Fault Diagnosis. Applied Sciences. 12(2). 818–818. 5 indexed citations
5.
Qian, Weiwei, Shunming Li, & Jiantao Lu. (2022). Deep Sparse Topology Network for Robust Bearing Fault Diagnosis by Maximizing Prior Knowledge Functions. IEEE Transactions on Industrial Informatics. 18(12). 8540–8550. 9 indexed citations
6.
Li, Shunming, et al.. (2022). A neural network with nuisance attribute projection: a novel method for bearing fault diagnosis under variable speed. Measurement Science and Technology. 33(7). 75010–75010. 7 indexed citations
7.
Li, Aijuan, et al.. (2022). Map Construction and Path Planning Method for a Mobile Robot Based on Multi-Sensor Information Fusion. Applied Sciences. 12(6). 2913–2913. 23 indexed citations
8.
Li, Shunming, et al.. (2022). A Novel Symmetric Stacked Autoencoder for Adversarial Domain Adaptation Under Variable Speed. IEEE Access. 10. 24678–24689. 9 indexed citations
9.
Li, Shunming, et al.. (2022). Weak Signal Detection Based on Combination of Sparse Representation and Singular Value Decomposition. Applied Sciences. 12(11). 5365–5365. 1 indexed citations
10.
Lu, Jiantao, et al.. (2022). Two-Channel Information Fusion Weak Signal Detection Based on Correntropy Method. Applied Sciences. 12(3). 1414–1414. 1 indexed citations
11.
Li, Shunming, Kun Xu, Xianglian Li, et al.. (2021). Adversarial domain adaptation of asymmetric mapping with CORAL alignment for intelligent fault diagnosis. Measurement Science and Technology. 33(5). 55101–55101. 37 indexed citations
12.
Lu, Jiantao, et al.. (2021). Fusion Method and Application of Several Source Vibration Fault Signal Spatio-Temporal Multi-Correlation. Applied Sciences. 11(10). 4318–4318. 14 indexed citations
13.
Li, Shunming, et al.. (2021). Deep domain adaptation with adversarial idea and coral alignment for transfer fault diagnosis of rolling bearing. Measurement Science and Technology. 32(9). 94009–94009. 25 indexed citations
14.
Zhang, Zongzhen, Shunming Li, Jiantao Lu, Jinrui Wang, & Xingxing Jiang. (2020). A Novel Unsupervised Learning Method Based on Cross-Normalization for Machinery Fault Diagnosis. IEEE Access. 8. 92407–92417. 7 indexed citations
15.
An, Zenghui, et al.. (2019). An intelligent fault diagnosis framework dealing with arbitrary length inputs under different working conditions. Measurement Science and Technology. 30(12). 125107–125107. 26 indexed citations
16.
Xu, Kun, et al.. (2019). A novel convolutional transfer feature discrimination network for unbalanced fault diagnosis under variable rotational speeds. Measurement Science and Technology. 30(10). 105107–105107. 31 indexed citations
17.
Wang, Jinrui, Shunming Li, Baokun Han, et al.. (2018). Construction of a batch-normalized autoencoder network and its application in mechanical intelligent fault diagnosis. Measurement Science and Technology. 30(1). 15106–15106. 57 indexed citations
18.
Li, Shunming, et al.. (2016). Uncertainty extraction based multi-fault diagnosis of rotating machinery. SHILAP Revista de lepidopterología. 1 indexed citations
19.
Cheng, Chun, et al.. (2015). On the analysis of a piecewise nonlinear-linear vibration isolator with high-static-low-dynamic-stiffness under base excitation. Journal of Vibroengineering. 17(7). 3453–3470. 10 indexed citations
20.
Li, Shunming. (2011). Engineering-oriented design method of micro-perforated absorber structure. Zhendong yu chongji. 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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