Linshan Jia

435 citations
7 papers · 303 · 2 hit papers · h-index 6

Impact in

Papers in

Linshan Jia

7 papers receiving 300 citations

Linshan Jia's Hit Papers

Causal Disentanglement Domain Generalization for time-series signal fault diagnosis 2024 · 59 citations
590+1+2Years since publication4080120

Peers

Linshan Jia
Comparison fields: 5 of 47
  • Control and Systems Engineering 234
  • Mechanical Engineering 117
  • Mechanics of Materials 63
  • Artificial Intelligence 55
  • Industrial and Manufacturing Engineering 17
Replace Kongliang Zhang with:
Kongliang Zhang China
Yadong Lu United States
Yuhang Ming China
Yiming He China
Shuilong He China
Matheus Araújo Marins Brazil
Joseph Mathew India
Thiago de M. Prego Brazil
M. Campos Brazil
Wanmeng Ding China
Linshan Jia relative to Kongliang Zhang China Kongliang Zhang's profile →
Citations per field
00.5×3.3×
Kongliang Zhang · 1×
Citations per year

Countries citing papers authored by Linshan Jia

Since Specialization
Citations

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

Fields of papers citing papers by Linshan Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Linshan Jia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Linshan Jia Line = papers co-authored together Linshan Jia links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1
GTFE-Net: A Gramian Time Frequency Enhancement CNN for bearing fault diagnosis
Hit paper breakdown →
2023126
2 202270
3
Causal Disentanglement Domain Generalization for time-series signal fault diagnosis
Hit paper breakdown →
202459
4 201920
5 201914
6 202412
7 20192

About Linshan Jia

Linshan Jia is a scholar working on Control and Systems Engineering, Mechanical Engineering, Mechanics of Materials, Civil and Structural Engineering and Computer Vision and Pattern Recognition, having authored 7 papers that have together received 303 indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (6 papers), Gear and Bearing Dynamics Analysis (3 papers), Fault Detection and Control Systems (3 papers), Engineering Diagnostics and Reliability (2 papers), Anomaly Detection Techniques and Applications (1 paper), Structural Health Monitoring Techniques (1 paper), Advanced machining processes and optimization (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Control and Systems Engineering (234 citations), Mechanical Engineering (117 citations), Mechanics of Materials (63 citations), Artificial Intelligence (55 citations) and Industrial and Manufacturing Engineering (17 citations). Linshan Jia has collaborated with scholars based in China and Hong Kong. Frequent co-authors include Tommy W. S. Chow, Yixuan Yuan, Yu Wang, Xiang Yuan Zheng, Qing Zhang, Jianghong Ma, Xiaohan Wei, Yi Wang, Sicong Zhang and Tangfei Tao. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Engineering Applications of Artificial Intelligence, Journal of Neural Engineering, Digital Signal Processing and Neural Networks.

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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