Dengyun Sun

801 total citations · 1 hit paper
20 papers, 623 citations indexed

About

Dengyun Sun is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Dengyun Sun has authored 20 papers receiving a total of 623 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Control and Systems Engineering, 14 papers in Mechanical Engineering and 7 papers in Mechanics of Materials. Recurrent topics in Dengyun Sun's work include Machine Fault Diagnosis Techniques (20 papers), Gear and Bearing Dynamics Analysis (13 papers) and Engineering Diagnostics and Reliability (6 papers). Dengyun Sun is often cited by papers focused on Machine Fault Diagnosis Techniques (20 papers), Gear and Bearing Dynamics Analysis (13 papers) and Engineering Diagnostics and Reliability (6 papers). Dengyun Sun collaborates with scholars based in China and Singapore. Dengyun Sun's co-authors include Zong Meng, Fengjie Fan, Yang Guan, Jingbo Liu, Ruxue Bai, Ying Zhang, Qian Li, Wei Cao, Zuozhou Pan and Shuang Liu and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Mechanical Systems and Signal Processing.

In The Last Decade

Dengyun Sun

17 papers receiving 605 citations

Hit Papers

An enhanced convolutional neural network for bearing faul... 2020 2026 2022 2024 2020 50 100 150 200
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. An enhanced convolutional neural network for bearing fault diagnosis based on time–frequency image
    2020 215 citations Ying Zhang, Ruxue Bai et al. Measurement profile →

Peers

Dengyun Sun
Song-Yu Han China
Sixiang Jia China
Xiaohui Gu China
Guoxi Sun China
Qiuyu Song China
Guoqiang Li China
Biliang Lu China
Daichao Wang China
Zhenling Mo China
Shengkang Yang China
Song-Yu Han China
Dengyun Sun
Citations per year, relative to Dengyun Sun Dengyun Sun (= 1×) peers Song-Yu Han

Countries citing papers authored by Dengyun Sun

Since Specialization
Citations

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

Fields of papers citing papers by Dengyun Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dengyun Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Dengyun Sun. A scholar is included among the top collaborators of Dengyun Sun 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 Dengyun Sun. Dengyun Sun 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.
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Sun, Dengyun, et al.. (2025). STFF-IFD: A novel multi-channel intelligent fault diagnosis based on data-driven spatio-temporal feature fusion. Expert Systems with Applications. 299. 130181–130181. 1 indexed citations
3.
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Meng, Zong, et al.. (2025). A novel sliding mixing graph contrastive domain adaptation method for fault diagnosis under time-varying speeds. Expert Systems with Applications. 270. 126576–126576. 2 indexed citations
5.
Zhang, Ying, et al.. (2025). A globally-locally consistent dynamically weighted joint optimization network for few-shot bearing fault diagnosis. Measurement Science and Technology. 36(8). 86109–86109.
6.
Guan, Yang, Zong Meng, Jimeng Li, et al.. (2024). A novel diagnostic framework based on vibration image encoding and multi-scale neural network. Expert Systems with Applications. 251. 124054–124054. 15 indexed citations
7.
Pan, Zuozhou, Yang Guan, Dengyun Sun, et al.. (2023). Fast fault diagnosis method of rolling bearings based on compression features in multi-sensor redundant observation environment. Applied Acoustics. 211. 109573–109573. 9 indexed citations
8.
Sun, Dengyun, et al.. (2023). Gearbox fault diagnosis based on generalized multivariate logarithmic regularization. Measurement Science and Technology. 34(6). 65103–65103. 6 indexed citations
9.
Liu, Jingbo, et al.. (2023). Local time-reassigned synchrosqueezing transform and its application in bearing fault characteristic extraction. Mechanical Systems and Signal Processing. 203. 110726–110726. 12 indexed citations
10.
Sun, Dengyun, Zong Meng, Yang Guan, et al.. (2023). Intelligent fault diagnosis scheme for rolling bearing based on domain adaptation in one dimensional feature matching. Applied Soft Computing. 146. 110669–110669. 20 indexed citations
11.
Meng, Zong, Dengyun Sun, Jingbo Liu, et al.. (2023). A two-stage domain alignment method for multi-source domain fault diagnosis. Measurement. 214. 112818–112818. 26 indexed citations
12.
Jin, Hailong, et al.. (2022). An improved two-stream compression convolution network for rolling bearing fault diagnosis. Measurement Science and Technology. 33(12). 125110–125110. 5 indexed citations
13.
Meng, Zong, Qian Li, Dengyun Sun, Wei Cao, & Fengjie Fan. (2022). An Intelligent Fault Diagnosis Method of Small Sample Bearing Based on Improved Auxiliary Classification Generative Adversarial Network. IEEE Sensors Journal. 22(20). 19543–19555. 49 indexed citations
14.
Guan, Yang, Zong Meng, Dengyun Sun, Jingbo Liu, & Fengjie Fan. (2022). Rolling bearing fault diagnosis based on information fusion and parallel lightweight convolutional network. Journal of Manufacturing Systems. 65. 811–821. 48 indexed citations
15.
Meng, Zong, et al.. (2022). Research on fault diagnosis method of MS-CNN rolling bearing based on local central moment discrepancy. Advanced Engineering Informatics. 54. 101797–101797. 31 indexed citations
16.
Guan, Yang, Zong Meng, & Dengyun Sun. (2021). Fault Diagnosis of Rolling Bearing with Imbalanced Small Sample Scenarios. 1–8. 3 indexed citations
17.
Xu, Quansheng, Jingbo Liu, Yang Guan, Dengyun Sun, & Zong Meng. (2021). Match-Extracting Chirplet Transform With Application to Bearing Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement. 70. 1–10. 12 indexed citations
18.
Guan, Yang, Zong Meng, Dengyun Sun, Jingbo Liu, & Fengjie Fan. (2021). 2MNet: Multi-sensor and multi-scale model toward accurate fault diagnosis of rolling bearing. Reliability Engineering & System Safety. 216. 108017–108017. 117 indexed citations
19.
Zhang, Ying, et al.. (2020). An enhanced convolutional neural network for bearing fault diagnosis based on time–frequency image. Measurement. 157. 107667–107667. 215 indexed citations breakdown →
20.

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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