Peiming Shi

3.1k total citations · 1 hit paper
133 papers, 2.4k citations indexed

About

Peiming Shi is a scholar working on Control and Systems Engineering, Mechanical Engineering and Statistical and Nonlinear Physics. According to data from OpenAlex, Peiming Shi has authored 133 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Control and Systems Engineering, 39 papers in Mechanical Engineering and 38 papers in Statistical and Nonlinear Physics. Recurrent topics in Peiming Shi's work include Machine Fault Diagnosis Techniques (48 papers), stochastic dynamics and bifurcation (34 papers) and Gear and Bearing Dynamics Analysis (23 papers). Peiming Shi is often cited by papers focused on Machine Fault Diagnosis Techniques (48 papers), stochastic dynamics and bifurcation (34 papers) and Gear and Bearing Dynamics Analysis (23 papers). Peiming Shi collaborates with scholars based in China, United States and Italy. Peiming Shi's co-authors include Dongying Han, Mengdi Li, Xuefang Xu, Jinghui Tian, Wenyue Zhang, Pei Li, Rongrong Fu, Ruixiong Li, Yue Yu and Huaishuang Shao and has published in prestigious journals such as Optics Letters, Expert Systems with Applications and IEEE Access.

In The Last Decade

Peiming Shi

129 papers receiving 2.3k citations

Hit Papers

A multi-source information transfer learning method with ... 2022 2026 2023 2024 2022 40 80 120
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. A multi-source information transfer learning method with subdomain adaptation for cross-domain fault diagnosis
    2022 139 citations Jinghui Tian, Mengdi Li et al. Knowledge-Based Systems profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peiming Shi China 29 1.1k 669 586 416 396 133 2.4k
Siliang Lu China 34 2.3k 2.1× 788 1.2× 1.4k 2.3× 623 1.5× 602 1.5× 117 3.8k
Fanrang Kong China 31 1.6k 1.4× 638 1.0× 1.0k 1.7× 539 1.3× 426 1.1× 71 2.4k
Yongbin Liu China 28 1.6k 1.5× 277 0.4× 1.0k 1.8× 200 0.5× 507 1.3× 130 2.6k
Shangbin Jiao China 19 382 0.3× 319 0.5× 167 0.3× 104 0.3× 84 0.2× 106 1.2k
Wenhu Huang China 33 2.3k 2.1× 104 0.2× 1.6k 2.8× 81 0.2× 1.1k 2.7× 113 3.8k
J. Bokor Hungary 31 3.0k 2.7× 150 0.2× 924 1.6× 281 0.7× 100 0.3× 386 4.6k
Takehisa Yairi Japan 14 617 0.6× 109 0.2× 308 0.5× 101 0.2× 193 0.5× 68 2.3k
Minqiang Xu China 36 2.7k 2.4× 66 0.1× 2.0k 3.4× 97 0.2× 963 2.4× 136 4.1k
Olav Egeland Norway 35 3.7k 3.3× 190 0.3× 1.0k 1.7× 46 0.1× 128 0.3× 205 5.2k

Countries citing papers authored by Peiming Shi

Since Specialization
Citations

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

Fields of papers citing papers by Peiming Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peiming Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Peiming Shi. A scholar is included among the top collaborators of Peiming Shi 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 Peiming Shi. Peiming Shi 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.
Shi, Peiming, et al.. (2025). KMDSAN: A novel method for cross-domain and unsupervised bearing fault diagnosis. Knowledge-Based Systems. 312. 113170–113170. 4 indexed citations
2.
Zhang, Bo, et al.. (2025). Fault diagnosis and classifications of rolling mill bearing-gear based on GADF-TL-ShuffleNet-V2. Journal of Vibration and Control. 1 indexed citations
3.
Zhang, Yu, Dongying Han, & Peiming Shi. (2024). Semi-supervised prototype network based on compact-uniform-sparse representation for rotating machinery few-shot class incremental fault diagnosis. Expert Systems with Applications. 255. 124660–124660. 18 indexed citations
4.
Shi, Peiming, et al.. (2024). TRNet: A trend and residual network utilizing novel hilly attention mechanism for wind speed prediction in complex scenario. Energy. 309. 133103–133103. 10 indexed citations
5.
Xu, Xuefang, et al.. (2024). Multi-source domain adaptation using diffusion denoising for bearing fault diagnosis under variable working conditions. Knowledge-Based Systems. 302. 112396–112396. 17 indexed citations
6.
Shi, Peiming, et al.. (2024). MGGSED-SSA: An improved sparse deconvolution method for rolling element bearing diagnosis. Applied Acoustics. 220. 109960–109960. 8 indexed citations
7.
Shi, Peiming, et al.. (2024). Transfer learning-based channel attention enhancement network combined with Gramian angular domain field for fault diagnosis. Measurement Science and Technology. 35(10). 106118–106118. 5 indexed citations
8.
Shi, Peiming, et al.. (2024). Rolling mill fault diagnosis under limited datasets. Knowledge-Based Systems. 291. 111579–111579. 1 indexed citations
9.
Shi, Peiming, et al.. (2023). TSN: A novel intelligent fault diagnosis method for bearing with small samples under variable working conditions. Reliability Engineering & System Safety. 240. 109575–109575. 38 indexed citations
10.
Zhang, Yu, et al.. (2023). Domain adaptation meta-learning network with discard-supplement module for few-shot cross-domain rotating machinery fault diagnosis. Knowledge-Based Systems. 268. 110484–110484. 32 indexed citations
11.
Shao, Huaishuang, et al.. (2023). Minimum entropy deconvolution enhanced by KLOF and phase editing for fault diagnosis of rotating machinery. Applied Acoustics. 209. 109423–109423. 14 indexed citations
12.
Zhang, Wenyue, Peiming Shi, Mengdi Li, et al.. (2023). A novel adaptive weak fault diagnosis method based on modulation periodic stochastic pooling networks. Chaos Solitons & Fractals. 173. 113588–113588. 8 indexed citations
13.
Shi, Peiming, et al.. (2023). Research on rolling bearing fault diagnosis method based on AMVMD and convolutional neural networks. Measurement. 217. 113028–113028. 29 indexed citations
14.
15.
Shi, Peiming, et al.. (2023). Characteristic frequency detection of steady-state visual evoked potentials based on filter bank second-order underdamped tristable stochastic resonance. Biomedical Signal Processing and Control. 84. 104817–104817. 10 indexed citations
16.
Shi, Peiming, et al.. (2023). A novel feature enhancement framework for rotating machinery fault identification under limited datasets. Applied Acoustics. 211. 109537–109537. 7 indexed citations
17.
18.
Zhang, Xingzhong, et al.. (2021). Vibration Characteristics of Hot Rolling Mill Rolls Based on Elastoplastic Hysteretic Deformation. Metals. 11(6). 869–869. 4 indexed citations
19.
Han, Dongying, et al.. (2017). Damage Identification of a Derrick Steel Structure Based on the HHT Marginal Spectrum Amplitude Curvature Difference. Shock and Vibration. 2017. 1–9. 6 indexed citations
20.
Shi, Peiming. (2009). Global Dynamic Characteristic of Nonlinear Torsional Vibration System under Harmonically Excitation. Chinese Journal of Mechanical Engineering. 22(1). 132–132. 16 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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