Xiukun Wei

1.9k total citations · 1 hit paper
74 papers, 1.4k citations indexed

About

Xiukun Wei is a scholar working on Control and Systems Engineering, Mechanical Engineering and Civil and Structural Engineering. According to data from OpenAlex, Xiukun Wei has authored 74 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Control and Systems Engineering, 35 papers in Mechanical Engineering and 26 papers in Civil and Structural Engineering. Recurrent topics in Xiukun Wei's work include Railway Engineering and Dynamics (25 papers), Machine Fault Diagnosis Techniques (25 papers) and Fault Detection and Control Systems (22 papers). Xiukun Wei is often cited by papers focused on Railway Engineering and Dynamics (25 papers), Machine Fault Diagnosis Techniques (25 papers) and Fault Detection and Control Systems (22 papers). Xiukun Wei collaborates with scholars based in China, Netherlands and Austria. Xiukun Wei's co-authors include Limin Jia, Luigi del Re, Dehua Wei, Yujie Li, Michel Verhaegen, Limin Jia, Yuxin Liu, Ziming Yang, Yong Qin and Hai Liu and has published in prestigious journals such as Nano Energy, Expert Systems with Applications and IEEE Access.

In The Last Decade

Xiukun Wei

71 papers receiving 1.4k citations

Hit Papers

Railway track fastener defect detection based on image pr... 2019 2026 2021 2023 2019 50 100 150 200
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. Railway track fastener defect detection based on image processing and deep learning techniques: A comparative study
    2019 245 citations Xiukun Wei, Dehua Wei et al. Engineering Applications of Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiukun Wei China 20 740 532 524 241 143 74 1.4k
Zhipeng Wang China 23 571 0.8× 324 0.6× 502 1.0× 180 0.7× 219 1.5× 111 1.5k
Luca Pugi Italy 29 1.2k 1.6× 232 0.4× 476 0.9× 588 2.4× 73 0.5× 217 2.7k
Argyrios Zolotas United Kingdom 19 392 0.5× 231 0.4× 917 1.8× 123 0.5× 58 0.4× 136 1.6k
Sheng Xiang China 18 640 0.9× 198 0.4× 965 1.8× 98 0.4× 85 0.6× 40 1.6k
R. Jegadeeshwaran India 19 635 0.9× 151 0.3× 377 0.7× 248 1.0× 33 0.2× 76 1.1k
Kunsoo Huh South Korea 23 472 0.6× 288 0.5× 686 1.3× 45 0.2× 253 1.8× 148 1.6k
Xiaoqiang Sun China 24 546 0.7× 365 0.7× 632 1.2× 35 0.1× 206 1.4× 93 1.5k
Yanjun Chen China 18 329 0.4× 77 0.1× 168 0.3× 132 0.5× 109 0.8× 83 956
Zhinong Jiang China 22 819 1.1× 190 0.4× 1.1k 2.1× 49 0.2× 66 0.5× 78 1.5k
Ngaiming Kwok Australia 22 486 0.7× 213 0.4× 224 0.4× 240 1.0× 611 4.3× 63 1.7k

Countries citing papers authored by Xiukun Wei

Since Specialization
Citations

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

Fields of papers citing papers by Xiukun Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiukun Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Xiukun Wei. A scholar is included among the top collaborators of Xiukun Wei 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 Xiukun Wei. Xiukun Wei 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.
2.
Yin, Shimin, et al.. (2024). Track Defects Recognition Based on Axle-Box Vibration Acceleration and Deep-Learning Techniques. Structural durability & health monitoring. 18(5). 623–640. 2 indexed citations
3.
Wei, Xiukun, et al.. (2024). Condition-based maintenance for multi-state systems with prognostic and deep reinforcement learning. Reliability Engineering & System Safety. 255. 110659–110659. 6 indexed citations
4.
Wei, Xiukun, et al.. (2024). A lightweight real-time accurate deformation detection approach for pantograph horns. Measurement. 236. 115128–115128.
5.
Wei, Xiukun, et al.. (2024). Biobjective Maintenance Strategy Optimization for Complex Multistate Systems Based on PH Distribution. IEEE Transactions on Reliability. 73(3). 1693–1707. 2 indexed citations
6.
Shen, Xing & Xiukun Wei. (2023). A Real-Time Subway Driver Action Sensoring and Detection Based on Lightweight ShuffleNetV2 Network. Sensors. 23(23). 9503–9503. 1 indexed citations
7.
Wei, Xiukun, et al.. (2023). High Precision Robust Real-Time Lightweight Approach for Railway Pantograph Slider Wear Estimation. IEEE Transactions on Intelligent Transportation Systems. 25(5). 3973–3985. 1 indexed citations
8.
Wei, Xiukun, et al.. (2023). Subtle defect detection on the surface of railway PCCS based on deep learning. Measurement. 225. 113964–113964. 2 indexed citations
9.
Wei, Dehua, et al.. (2023). RTLSeg: A novel multi-component inspection network for railway track line based on instance segmentation. Engineering Applications of Artificial Intelligence. 119. 105822–105822. 21 indexed citations
10.
Wei, Dehua, Xiukun Wei, & Limin Jia. (2022). Automatic Defect Description of Railway Track Line Image Based on Dense Captioning. Sensors. 22(17). 6419–6419. 10 indexed citations
11.
Wei, Xiukun, et al.. (2022). Joint Maintenance Strategy Optimization for Railway Bogie Wheelset. Applied Sciences. 12(14). 6934–6934. 4 indexed citations
12.
Wei, Xiukun, et al.. (2020). RUL Prediction of Railway PCCS Based on Wiener Process Model with Unequal Interval Wear Data. Applied Sciences. 10(5). 1616–1616. 12 indexed citations
13.
Wei, Xiukun, et al.. (2020). Multi-Target Defect Identification for Railway Track Line Based on Image Processing and Improved YOLOv3 Model. IEEE Access. 8. 61973–61988. 96 indexed citations
14.
Li, Sai, Xiukun Wei, Zhe Zhang, Limin Jia, & Junyan Yu. (2019). Subway Station Capacity Maintained by Optimizing a Maintenance Schedule of Key Equipment. Applied Sciences. 9(7). 1386–1386. 1 indexed citations
15.
Wei, Xiukun, et al.. (2019). Defect Detection of Pantograph Slide Based on Deep Learning and Image Processing Technology. IEEE Transactions on Intelligent Transportation Systems. 21(3). 947–958. 83 indexed citations
16.
Qin, Yong, et al.. (2019). Railway vehicle bearings risk monitoring based on normal region estimation for no-fault data situations. Journal of Transportation Safety & Security. 13(10). 1047–1065. 3 indexed citations
17.
Wei, Xiukun, Limin Jia, Kun Guo, & Sheng Wu. (2014). Fault Isolation for Urban Railway Vehicle Suspension Systems. IFAC Proceedings Volumes. 47(3). 12122–12127. 2 indexed citations
18.
Wei, Xiukun, Ying Guo, Limin Jia, & Hai Liu. (2013). Fault detection of rail vehicle suspension system based on CPCA. 700–705. 5 indexed citations
19.
Wei, Xiukun, Hai Liu, & Limin Jia. (2012). Fault detection of urban rail vehicle suspension system based on acceleration measurements. 1129–1134. 15 indexed citations
20.
Wei, Xiukun & Michel Verhaegen. (2010). LMI solutions to the mixed ℋ−/ℋ∞fault detection observer design for linear parameter‐varying systems. International Journal of Adaptive Control and Signal Processing. 25(2). 114–136. 44 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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