Xiaoan Yan
- Control and Systems Engineering top 0.2%
- Mechanical Engineering top 0.5%
- Mechanics of Materials top 1%
- Artificial Intelligence top 2%
- Electrical and Electronic Engineering top 10%
- Co-authors
- Minping JiaYadong XuBeibei SunZheng LiuLing XiangXianbo WangZhi-Xin YangYing Liu
- Topics
- Machine Fault Diagnosis Techniques (83 papers)Gear and Bearing Dynamics Analysis (50 papers)Engineering Diagnostics and Reliability (29 papers)
In The Last Decade
Xiaoan Yan
91 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Control and Systems Engineering 3.0k
- Mechanical Engineering 1.9k
- Mechanics of Materials 1.1k
- Artificial Intelligence 502
- Electrical and Electronic Engineering 348
Countries citing papers authored by Xiaoan Yan
This map shows the geographic impact of Xiaoan Yan'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 Xiaoan Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoan Yan more than expected).
Fields of papers citing papers by Xiaoan Yan
This network shows the impact of papers produced by Xiaoan Yan. 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 Xiaoan Yan. The network helps show where Xiaoan Yan may publish in the future.
Co-authorship network of co-authors of Xiaoan Yan
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoan Yan. A scholar is included among the top collaborators of Xiaoan Yan 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 Xiaoan Yan. Xiaoan Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 10 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | MRCFN: A multi-sensor residual convolutional fusion network for intelligent fault diagnosis of bearings in noisy and small sample scenariosbreakdown → | 65 |
| 7 | 10 | |
| 8 | 8 | |
| 9 | 8 | |
| 10 | 8 | |
| 11 | CDTFAFN: A novel coarse-to-fine dual-scale time-frequency attention fusion network for machinery vibro-acoustic fault diagnosisbreakdown → | 44 |
| 12 | 8 | |
| 13 | 7 | |
| 14 | CFCNN: A novel convolutional fusion framework for collaborative fault identification of rotating machinerybreakdown → | 136 |
| 15 | 3 | |
| 16 | 22 | |
| 17 | 16 | |
| 18 | 58 | |
| 19 | 16 | |
| 20 | 40 |
About Xiaoan Yan
Xiaoan Yan is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials, having authored 94 papers that have together received 4.0k indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (83 papers), Gear and Bearing Dynamics Analysis (50 papers) and Engineering Diagnostics and Reliability (29 papers). The work is most often cited by research in Control and Systems Engineering (3.0k citations), Mechanical Engineering (1.9k citations) and Mechanics of Materials (1.1k citations). Xiaoan Yan has collaborated with scholars based in China, Canada and Australia. Frequent co-authors include Minping Jia, Yadong Xu, Beibei Sun, Zheng Liu, Ling Xiang, Xianbo Wang, Zhi-Xin Yang, Ying Liu, Daoming She and Maoyou Ye. Their work appears in journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and Energy Conversion and Management.
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.