Guowei Tu

425 citations
9 papers · 308 · 1 hit paper · h-index 8

Impact in

Papers in

Guowei Tu

9 papers receiving 303 citations

Guowei Tu's Hit Papers

TFN: An interpretable neural network with time-frequency transform embedded for intelligent fault diagnosis 2023 · 122 citations
1220+1+2Years since publication4080120

Peers

Guowei Tu
Comparison fields: 5 of 41
  • Control and Systems Engineering 145
  • Mechanical Engineering 143
  • Mechanics of Materials 74
  • Industrial and Manufacturing Engineering 19
  • Civil and Structural Engineering 27
Replace N. Irani with:
N. Irani Netherlands
Lixiao Wu China
Shijie Hu China
Constantine Tarawneh United States
Xiangyi Geng China
Kleiton de Morais Sousa Brazil
Chunli Lei China
Bintao Sun China
Dianhai Zhang China
Guowei Tu relative to N. Irani Netherlands N. Irani's profile →
Citations per field
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N. Irani · 1×
Citations per year

Countries citing papers authored by Guowei Tu

Since Specialization
Citations

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

Fields of papers citing papers by Guowei Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Guowei Tu, 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 Guowei Tu Line = papers co-authored together Guowei Tu links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
TFN: An interpretable neural network with time-frequency transform embedded for intelligent fault diagnosis
Hit paper breakdown →
2023122
2 202260
3 202333
4 202129
5 202027
6 202114
7 202311
8 20219
9 20243

About Guowei Tu

Guowei Tu is a scholar working on Control and Systems Engineering, Mechanical Engineering, Civil and Structural Engineering, Atomic and Molecular Physics, and Optics and Mechanics of Materials, having authored 9 papers that have together received 308 indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (5 papers), Advanced machining processes and optimization (3 papers), Structural Health Monitoring Techniques (2 papers), Gear and Bearing Dynamics Analysis (2 papers), Engineering Diagnostics and Reliability (1 paper), Topological Materials and Phenomena (1 paper), Advanced Machining and Optimization Techniques (1 paper) and Metamaterials and Metasurfaces Applications (1 paper). The work is most often cited by research in Control and Systems Engineering (145 citations), Mechanical Engineering (143 citations), Mechanics of Materials (74 citations), Industrial and Manufacturing Engineering (19 citations) and Civil and Structural Engineering (27 citations). Guowei Tu has collaborated with scholars based in China and United States. Frequent co-authors include Zhike Peng, Xingjian Dong, Baoxuan Zhao, Changming Cheng, Dong Wang, Kangkang Chen, Yifan Huangfu, Xinhua Long, Shiqian Chen and Lan Hu. Their work appears in journals such as International Journal of Mechanical Sciences, Journal of Vibration and Control, Journal of Sound and Vibration, International Journal of Machine Tools and Manufacture and Journal of the Mechanics and Physics of Solids.

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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