Changqing Shen

8.4k total citations · 8 hit papers
199 papers, 6.8k citations indexed

About

Changqing Shen is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Changqing Shen has authored 199 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 172 papers in Control and Systems Engineering, 118 papers in Mechanical Engineering and 46 papers in Mechanics of Materials. Recurrent topics in Changqing Shen's work include Machine Fault Diagnosis Techniques (164 papers), Gear and Bearing Dynamics Analysis (82 papers) and Fault Detection and Control Systems (56 papers). Changqing Shen is often cited by papers focused on Machine Fault Diagnosis Techniques (164 papers), Gear and Bearing Dynamics Analysis (82 papers) and Fault Detection and Control Systems (56 papers). Changqing Shen collaborates with scholars based in China, Singapore and Hong Kong. Changqing Shen's co-authors include Zhongkui Zhu, Dong Wang, Liang Chen, Jun Zhu, Weiguo Huang, Juanjuan Shi, Xiaojie Guo, Nan Chen, Xingxing Jiang and Jun Wang and has published in prestigious journals such as Carbon, Chemical Engineering Journal and IEEE Transactions on Industrial Electronics.

In The Last Decade

Changqing Shen

189 papers receiving 6.6k citations

Hit Papers

Hierarchical adaptive deep convolution neural network and... 2016 2026 2019 2022 2016 2020 2020 2019 2021 200 400 600
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. Hierarchical adaptive deep convolution neural network and its application to bearing fault diagnosis
    2016 630 citations Liang Chen, Changqing Shen et al. Measurement profile →
  2. A new data-driven transferable remaining useful life prediction approach for bearing under different working conditions
    2020 268 citations Jun Zhu, Changqing Shen et al. profile →
  3. Multi-scale deep intra-class transfer learning for bearing fault diagnosis
    2020 267 citations Changqing Shen, Min Xia et al. Reliability Engineering & System Safety profile →
  4. A New Deep Transfer Learning Method for Bearing Fault Diagnosis Under Different Working Conditions
    2019 229 citations Jun Zhu, Changqing Shen et al. IEEE Sensors Journal profile →
  5. Bearing fault diagnosis via generalized logarithm sparse regularization
    2021 184 citations Weiguo Huang, Juanjuan Shi et al. profile →
  6. Adversarial Domain-Invariant Generalization: A Generic Domain-Regressive Framework for Bearing Fault Diagnosis Under Unseen Conditions
    2021 164 citations Liang Chen, Qi Li et al. profile →
  7. Central frequency mode decomposition and its applications to the fault diagnosis of rotating machines
    2022 109 citations Xingxing Jiang, Changqing Shen et al. profile →
  8. Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions
    2023 83 citations Qi Li, Liang Chen et al. Reliability Engineering & System Safety profile →

Peers

Changqing Shen
Jinglong Chen China
Hongkai Jiang China
Minping Jia China
Ming Zhao China
Feng Jia China
Chuang Sun China
Zhuyun Chen China
Zhongkui Zhu China
Lingli Cui China
Haidong Shao China
Jinglong Chen China
Changqing Shen
Citations per year, relative to Changqing Shen Changqing Shen (= 1×) peers Jinglong Chen

Countries citing papers authored by Changqing Shen

Since Specialization
Citations

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

Fields of papers citing papers by Changqing Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changqing Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Changqing Shen. A scholar is included among the top collaborators of Changqing Shen 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 Changqing Shen. Changqing Shen 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.
Shen, Changqing, et al.. (2025). A new lifelong learning method based on dual distillation for bearing diagnosis with incremental fault types. Advanced Engineering Informatics. 65. 103136–103136. 8 indexed citations
2.
Shen, Changqing, et al.. (2025). Dynamic branch layer fusion: A new continual learning method for rotating machinery fault diagnosis. Knowledge-Based Systems. 313. 113177–113177. 8 indexed citations
3.
Chen, Yuting, Juanjuan Shi, Changqing Shen, et al.. (2025). Time-frequency aware feature disentanglement learning for intelligent bearing fault diagnosis under variable speed conditions. Expert Systems with Applications. 303. 130664–130664.
4.
Zhu, Hongyan, et al.. (2024). Reserving embedding space for new fault types: A new continual learning method for bearing fault diagnosis. Reliability Engineering & System Safety. 252. 110433–110433. 9 indexed citations
5.
Li, Qi, et al.. (2024). Fault diagnosis for ball screws in industrial robots under variable and inaccessible working conditions with non-vibration signals. Advanced Engineering Informatics. 62. 102617–102617. 8 indexed citations
6.
Sun, Shilong, et al.. (2024). Dynamics modeling and fault diagnosis of flexible thin-walled elliptical bearings in harmonic reducers. Measurement. 238. 115378–115378. 8 indexed citations
7.
Shen, Changqing, Fangzhu Qing, & Xuesong Li. (2024). The etching effect of oxygen during the cooling process of graphene CVD synthesis. Carbon. 230. 119654–119654. 5 indexed citations
8.
9.
Zhang, Yan, et al.. (2024). Adaptive feature consolidation residual network for exemplar-free continuous diagnosis of rotating machinery with fault-type increments. Advanced Engineering Informatics. 62. 102715–102715. 7 indexed citations
10.
Shen, Changqing, Bojian Chen, Juanjuan Shi, et al.. (2024). A new feature boosting based continual learning method for bearing fault diagnosis with incremental fault types. Advanced Engineering Informatics. 61. 102469–102469. 30 indexed citations
11.
Chen, Liang, et al.. (2024). Joint Domain Adaptation-Based Lightweight Approach for Cross-Domain Diagnosis Compatible With Different Devices and Multimodal Sensing. IEEE Sensors Journal. 24(17). 28373–28382. 3 indexed citations
12.
Shi, Juanjuan, Xingxing Jiang, Chuan Li, et al.. (2024). Dynamic modeling considering time-varying contact pairs and parameterized defects of deep groove ball bearings for its vibration characteristic analysis. Nonlinear Dynamics. 112(20). 17781–17809. 9 indexed citations
13.
14.
Chen, Wenhe, et al.. (2022). Intelligent machine fault diagnosis with effective denoising using EEMD-ICA- FuzzyEn and CNN. International Journal of Production Research. 61(23). 8252–8264. 27 indexed citations
15.
Wang, Rui, Weiguo Huang, Jun Wang, Changqing Shen, & Zhongkui Zhu. (2022). Multisource Domain Feature Adaptation Network for Bearing Fault Diagnosis Under Time-Varying Working Conditions. IEEE Transactions on Instrumentation and Measurement. 71. 1–10. 62 indexed citations
16.
Hou, Bingchang, et al.. (2022). Statistical learning modeling based health indicator construction for machine condition monitoring. Measurement Science and Technology. 34(1). 14008–14008. 5 indexed citations
17.
Li, Ruixian, et al.. (2021). Intelligent Bearing Fault Diagnosis Based on Scaled Ramanujan Filter Banks in Noisy Environments. IEEE Transactions on Instrumentation and Measurement. 70. 1–13. 9 indexed citations
18.
Shen, Changqing, et al.. (2020). A new transferable bearing fault diagnosis approach with adaptive manifold embedded distribution alignment. Measurement Science and Technology. 32(3). 34004–34004. 5 indexed citations
19.
Li, Qi, Liang Chen, Changqing Shen, Bingru Yang, & Zhongkui Zhu. (2019). Enhanced generative adversarial networks for fault diagnosis of rotating machinery with imbalanced data. Measurement Science and Technology. 30(11). 115005–115005. 52 indexed citations
20.
Shen, Changqing, Fangzhu Qing, Xiaobin Niu, et al.. (2019). Criteria for the growth of large-area adlayer-free monolayer graphene films by chemical vapor deposition. Journal of Materiomics. 5(3). 463–470. 22 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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