Yuanhang Chen
- Control and Systems Engineering top 0.2%
- Mechanical Engineering top 1%
- Mechanics of Materials top 1%
- Artificial Intelligence top 5%
- Civil and Structural Engineering top 5%
- Co-authors
- Wěi ZhāngZhujun ZhangGaoliang PengChuanhao LiZhiyu ZhuHuijun GaoSijue LiChunli Yang
- Topics
- Additive Manufacturing Materials and Processes (6 papers)Machine Fault Diagnosis Techniques (5 papers)Titanium Alloys Microstructure and Properties (4 papers)
In The Last Decade
Yuanhang Chen
14 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Control and Systems Engineering 2.5k
- Mechanical Engineering 1.9k
- Mechanics of Materials 990
- Artificial Intelligence 349
- Civil and Structural Engineering 265
Countries citing papers authored by Yuanhang Chen
This map shows the geographic impact of Yuanhang Chen'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 Yuanhang Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuanhang Chen more than expected).
Fields of papers citing papers by Yuanhang Chen
This network shows the impact of papers produced by Yuanhang Chen. 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 Yuanhang Chen. The network helps show where Yuanhang Chen may publish in the future.
Co-authorship network of co-authors of Yuanhang Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Yuanhang Chen. A scholar is included among the top collaborators of Yuanhang Chen 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 Yuanhang Chen. Yuanhang Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 13 | |
| 5 | 18 | |
| 6 | 30 | |
| 7 | 32 | |
| 8 | 56 | |
| 9 | 42 | |
| 10 | A novel deep learning method based on attention mechanism for bearing remaining useful life predictionbreakdown → | 297 |
| 11 | 51 | |
| 12 | 105 | |
| 13 | A convolutional neural network based on a capsule network with strong generalization for bearing fault diagnosisbreakdown → | 305 |
| 14 | A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signalsbreakdown → | 1212 |
| 15 | A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working loadbreakdown → | 1057 |
About Yuanhang Chen
Yuanhang Chen is a scholar working on Mechanical Engineering, Control and Systems Engineering and Materials Chemistry, having authored 15 papers that have together received 3.2k indexed citations. Recurring topics across this work include Additive Manufacturing Materials and Processes (6 papers), Machine Fault Diagnosis Techniques (5 papers) and Titanium Alloys Microstructure and Properties (4 papers). The work is most often cited by research in Control and Systems Engineering (2.5k citations), Mechanical Engineering (1.9k citations) and Mechanics of Materials (990 citations). Yuanhang Chen has collaborated with scholars based in China and Singapore. Frequent co-authors include Wěi Zhāng, Zhujun Zhang, Gaoliang Peng, Chuanhao Li, Chuanhao Li, Gaoliang Peng, Zhiyu Zhu, Huijun Gao, Sijue Li and Chunli Yang. Their work appears in journals such as Materials Science and Engineering A, Sensors and Journal of Alloys and Compounds.
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.