Tongyang Pan

2.3k total citations · 3 hit papers
49 papers, 1.8k citations indexed

About

Tongyang Pan is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Tongyang Pan has authored 49 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Control and Systems Engineering, 29 papers in Mechanical Engineering and 19 papers in Mechanics of Materials. Recurrent topics in Tongyang Pan's work include Machine Fault Diagnosis Techniques (40 papers), Gear and Bearing Dynamics Analysis (19 papers) and Fault Detection and Control Systems (15 papers). Tongyang Pan is often cited by papers focused on Machine Fault Diagnosis Techniques (40 papers), Gear and Bearing Dynamics Analysis (19 papers) and Fault Detection and Control Systems (15 papers). Tongyang Pan collaborates with scholars based in China, Canada and Singapore. Tongyang Pan's co-authors include Jinglong Chen, Tianci Zhang, Shuilong He, Haixin Lv, Zitong Zhou, Yong Feng, Jingsong Xie, Shen Liu, Yuanhong Chang and Fudong Li and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and Renewable Energy.

In The Last Decade

Tongyang Pan

48 papers receiving 1.7k citations

Hit Papers

Meta-learning as a promis... 2021 2026 2022 2024 2021 2021 2022 50 100 150
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. Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects
    2021 186 citations Yong Feng, Jinglong Chen et al. profile →
  2. Generative adversarial network in mechanical fault diagnosis under small sample: A systematic review on applications and future perspectives
    2021 180 citations Tongyang Pan, Jinglong Chen et al. ISA Transactions profile →
  3. Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
    2022 156 citations Haixin Lv, Jinglong Chen et al. Measurement profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Tongyang Pan 1.4k 703 432 370 209 49 1.8k
Tianci Zhang 1.5k 1.1× 793 1.1× 499 1.2× 420 1.1× 221 1.1× 45 2.0k
Weining Lu 1.3k 0.9× 721 1.0× 402 0.9× 355 1.0× 133 0.6× 33 1.8k
Govind Vashishtha 976 0.7× 772 1.1× 324 0.8× 305 0.8× 259 1.2× 83 1.7k
Yixiao Liao 1.5k 1.1× 854 1.2× 419 1.0× 458 1.2× 107 0.5× 19 1.9k
Jipu Li 1.9k 1.4× 1.0k 1.4× 634 1.5× 574 1.6× 155 0.7× 53 2.4k
Haixin Lv 993 0.7× 486 0.7× 404 0.9× 277 0.7× 125 0.6× 19 1.3k
Shen Yan 1.2k 0.8× 532 0.8× 369 0.9× 360 1.0× 130 0.6× 21 1.5k
Jinyang Jiao 1.8k 1.3× 1.0k 1.4× 415 1.0× 498 1.3× 138 0.7× 46 2.1k
Yiming Xiao 1.1k 0.8× 577 0.8× 333 0.8× 339 0.9× 114 0.5× 23 1.4k

Countries citing papers authored by Tongyang Pan

Since Specialization
Citations

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

Fields of papers citing papers by Tongyang Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tongyang Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Tongyang Pan. A scholar is included among the top collaborators of Tongyang Pan 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 Tongyang Pan. Tongyang Pan 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.
Gong, Jing, et al.. (2025). BMTM-net: A rotating machinery fault diagnosis network based on 2D-1D fusion with bidirectional multi-granularity transformer-mamba. Neurocomputing. 656. 131293–131293. 1 indexed citations
2.
Xie, Jingsong, et al.. (2025). A pruning-aware dynamic slimmable network using meta-gradients for high-speed train bogie bearing fault diagnosis. ISA Transactions. 160. 196–204. 3 indexed citations
3.
4.
Li, Yuyan, et al.. (2025). A temporal cross-contrastive self-supervised learning framework for high-speed train bearing fault diagnosis: addressing limited labeling and speed variability. Engineering Applications of Artificial Intelligence. 158. 111537–111537. 1 indexed citations
5.
Wang, Tiantian, et al.. (2025). A Source Domain Adaptive Method for Transfer-Learning-Based Fault Diagnosis of Train Bogie Bearings at Higher Speeds. IEEE Transactions on Instrumentation and Measurement. 74. 1–11. 2 indexed citations
6.
Wang, Tiantian, et al.. (2025). Advanced framework for intelligent fault diagnosis in rotary machinery with out-of-distribution recognition. Measurement Science and Technology. 36(2). 26140–26140. 1 indexed citations
7.
Xie, Jingsong, et al.. (2024). DiffPhysiNet: A Bearing Diagnostic Framework Based on Physics-Driven Diffusion Network for Unseen Working Conditions. PHM Society European Conference. 8(1). 10–10. 2 indexed citations
8.
Yang, J. N., Zhiqiang Gan, Tiantian Wang, et al.. (2024). Multi-source dynamic adaptive domain generalization network for crack detection under unknown temperature environment. Measurement. 240. 115588–115588. 1 indexed citations
9.
Chen, Jinglong, et al.. (2024). A batch-adapted cost-sensitive contrastive feature learning network for industrial diagnosis with extremely imbalanced data. Measurement. 244. 116478–116478. 2 indexed citations
10.
Pan, Tongyang, et al.. (2024). A meta-weighted network equipped with uncertainty estimations for remaining useful life prediction of turbopump bearings. Expert Systems with Applications. 252. 124161–124161. 4 indexed citations
11.
12.
Xie, Jingsong, et al.. (2024). A Simulated-to-Real Transfer Fault Diagnosis Method Based on Prototype Clustering Subdomain Adversarial Adaptation Network for HST Bogie Bearing. IEEE Transactions on Instrumentation and Measurement. 73. 1–13. 3 indexed citations
13.
Chen, Jinglong, et al.. (2024). Uncertainty Estimation Pseudo-Labels Guided Source-Free Domain Adaptation for Cross-Domain Remaining Useful Life Prediction in IIoT. IEEE Internet of Things Journal. 1–1. 1 indexed citations
14.
Li, Yuyan, et al.. (2024). A simulation data-driven semi-supervised framework based on MK-KNN graph and ESSGAT for bearing fault diagnosis. ISA Transactions. 155. 261–273. 12 indexed citations
15.
Feng, Yong, Chaoxin Zheng, Jinglong Chen, et al.. (2024). Beyond deep features: Fast random wavelet kernel convolution for weak-fault feature extraction of rotating machinery. Mechanical Systems and Signal Processing. 224. 112057–112057. 5 indexed citations
16.
Pan, Tongyang, Jinglong Chen, Tianci Zhang, et al.. (2021). Generative adversarial network in mechanical fault diagnosis under small sample: A systematic review on applications and future perspectives. ISA Transactions. 128(Pt B). 1–10. 180 indexed citations breakdown →
17.
Liu, Shen, et al.. (2020). LOSGAN: latent optimized stable GAN for intelligent fault diagnosis with limited data in rotating machinery. Measurement Science and Technology. 32(4). 45101–45101. 42 indexed citations
18.
19.
Lv, Haixin, et al.. (2020). SDA: Regularization with Cut-Flip and Mix-Normal for machinery fault diagnosis under small dataset. ISA Transactions. 111. 337–349. 25 indexed citations
20.
Li, Fudong, Jinglong Chen, Jun Pan, & Tongyang Pan. (2020). Cross-domain learning in rotating machinery fault diagnosis under various operating conditions based on parameter transfer. Measurement Science and Technology. 31(8). 85104–85104. 38 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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