Dingliang Chen

1.0k total citations · 2 hit papers
18 papers, 778 citations indexed

About

Dingliang Chen is a scholar working on Control and Systems Engineering, Mechanical Engineering and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Dingliang Chen has authored 18 papers receiving a total of 778 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Control and Systems Engineering, 9 papers in Mechanical Engineering and 4 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Dingliang Chen's work include Machine Fault Diagnosis Techniques (14 papers), Gear and Bearing Dynamics Analysis (5 papers) and Mechanical Failure Analysis and Simulation (5 papers). Dingliang Chen is often cited by papers focused on Machine Fault Diagnosis Techniques (14 papers), Gear and Bearing Dynamics Analysis (5 papers) and Mechanical Failure Analysis and Simulation (5 papers). Dingliang Chen collaborates with scholars based in China, Canada and Germany. Dingliang Chen's co-authors include Yi Qin, Jianghong Zhou, Sheng Xiang, Caichao Zhu, Yi Wang, C WANG, Chunlei Wu, Fuqiang Liu, Quan Qian and Jun Luo and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Renewable Energy and Information Sciences.

In The Last Decade

Dingliang Chen

17 papers receiving 746 citations

Hit Papers

Gated Dual Attention Unit Neural Networks for Remaining U... 2020 2026 2022 2024 2020 2022 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dingliang Chen China 10 563 324 151 135 91 18 778
Mingliang Suo China 14 350 0.6× 119 0.4× 61 0.4× 50 0.4× 120 1.3× 39 569
Indranil Roychoudhury United States 17 736 1.3× 125 0.4× 61 0.4× 215 1.6× 230 2.5× 65 1.0k
Beike Zhang China 11 528 0.9× 288 0.9× 163 1.1× 37 0.3× 120 1.3× 35 737
Yunwen Feng China 14 197 0.3× 172 0.5× 223 1.5× 102 0.8× 52 0.6× 61 755
Pin Lim Singapore 7 784 1.4× 271 0.8× 162 1.1× 335 2.5× 255 2.8× 8 1.1k
Gregory J. Kacprzynski United States 15 506 0.9× 127 0.4× 130 0.9× 166 1.2× 93 1.0× 33 756
Edward Balaban United States 15 882 1.6× 237 0.7× 109 0.7× 220 1.6× 203 2.2× 34 1.2k
Xihui Liang China 6 344 0.6× 235 0.7× 135 0.9× 53 0.4× 58 0.6× 9 616
Xiaohong Wang China 13 428 0.8× 227 0.7× 100 0.7× 23 0.2× 55 0.6× 49 634
Sheraz Ali Khan South Korea 15 612 1.1× 396 1.2× 222 1.5× 197 1.5× 53 0.6× 27 872

Countries citing papers authored by Dingliang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Dingliang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dingliang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Dingliang Chen. A scholar is included among the top collaborators of Dingliang 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 Dingliang Chen. Dingliang Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Chen, Dingliang, Jianghong Zhou, & Yi Qin. (2025). Unsupervised Health Indicator Fusing Time and Frequency Domain Information and Its Application to Remaining Useful Life Prediction. IEEE Transactions on Instrumentation and Measurement. 74. 1–12. 4 indexed citations
2.
3.
Chen, Dingliang, Yi Wang, Yi Chai, Yuejian Chen, & Yi Qin. (2025). A polynomial speed normalized health indicator for both incipient fault detection and prognosis of variable-speed wind turbine bearings. Advanced Engineering Informatics. 66. 103455–103455. 2 indexed citations
4.
Zhou, Jianghong, et al.. (2025). Benchmark transformation neural network for health indicator construction under time-varying speed and its application in machinery prognostics. Reliability Engineering & System Safety. 257. 110823–110823. 2 indexed citations
5.
Chen, Dingliang, Yi Chai, Yongfang Mao, & Yi Qin. (2024). Unsupervised health indicator construction by a new Gaussian-student’s t-distribution mixture model and its application. Advanced Engineering Informatics. 62. 102863–102863. 2 indexed citations
6.
Lv, Wang, Dingliang Chen, Yongfang Mao, & Qin Yi. (2024). A zero-shot attribute-embedded model with a feature difference mapping sigmoid function for compound fault diagnosis of rotating machinery. ISA Transactions. 157. 451–465. 3 indexed citations
8.
Chen, Dingliang, et al.. (2024). A lognormal-normal mixture model for unsupervised health indicator construction and its application into gear remaining useful life prediction. Mechanical Systems and Signal Processing. 220. 111699–111699. 9 indexed citations
9.
Zhou, Jianghong, et al.. (2024). Continuous Remaining Useful Life Prediction by Self-Guided Attention Convolutional Neural Network and Memory Consciousness Adjustment. IEEE Internet of Things Journal. 11(19). 31947–31958. 9 indexed citations
10.
Chen, Dingliang, et al.. (2023). A novel transfer gear life prediction method by the cross-condition health indicator and nested hierarchical binary-valued network. Reliability Engineering & System Safety. 237. 109390–109390. 20 indexed citations
11.
Zhu, Yongchao, Caichao Zhu, Jianjun Tan, et al.. (2022). Fault detection of offshore wind turbine gearboxes based on deep adaptive networks via considering Spatio-temporal fusion. Renewable Energy. 200. 1023–1036. 14 indexed citations
12.
Zhou, Jianghong, Yi Qin, Dingliang Chen, Fuqiang Liu, & Quan Qian. (2022). Remaining useful life prediction of bearings by a new reinforced memory GRU network. Advanced Engineering Informatics. 53. 101682–101682. 108 indexed citations breakdown →
13.
Chen, Dingliang, Yi Qin, Quan Qian, Yi Wang, & Fuqiang Liu. (2022). Transfer life prediction of gears by cross-domain health indicator construction and multi-hierarchical long-term memory augmented network. Reliability Engineering & System Safety. 230. 108916–108916. 30 indexed citations
14.
Chen, Dingliang, Yi Qin, Jun Luo, & Sheng Xiang. (2021). Gated Adaptive Hierarchical Attention Unit Neural Networks for the Life Prediction of Servo Motors. IEEE Transactions on Industrial Electronics. 69(9). 9451–9461. 31 indexed citations
15.
Qin, Yi, Jianghong Zhou, & Dingliang Chen. (2021). Unsupervised Health Indicator Construction by a Novel Degradation-Trend-Constrained Variational Autoencoder and Its Applications. IEEE/ASME Transactions on Mechatronics. 27(3). 1447–1456. 87 indexed citations
16.
Chen, Dingliang, Yi Qin, Yi Wang, & Jianghong Zhou. (2020). Health indicator construction by quadratic function-based deep convolutional auto-encoder and its application into bearing RUL prediction. ISA Transactions. 114. 44–56. 136 indexed citations
17.
Qin, Yi, Dingliang Chen, Sheng Xiang, & Caichao Zhu. (2020). Gated Dual Attention Unit Neural Networks for Remaining Useful Life Prediction of Rolling Bearings. IEEE Transactions on Industrial Informatics. 17(9). 6438–6447. 215 indexed citations breakdown →
18.
WANG, C, Chunlei Wu, & Dingliang Chen. (2008). A systematic study on attribute reduction with rough sets based on general binary relations. Information Sciences. 178(9). 2237–2261. 89 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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