Dikang Peng

483 total citations · 1 hit paper
14 papers, 341 citations indexed

About

Dikang Peng is a scholar working on Control and Systems Engineering, Mechanical Engineering and Civil and Structural Engineering. According to data from OpenAlex, Dikang Peng has authored 14 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Control and Systems Engineering, 12 papers in Mechanical Engineering and 8 papers in Civil and Structural Engineering. Recurrent topics in Dikang Peng's work include Machine Fault Diagnosis Techniques (14 papers), Gear and Bearing Dynamics Analysis (9 papers) and Structural Health Monitoring Techniques (8 papers). Dikang Peng is often cited by papers focused on Machine Fault Diagnosis Techniques (14 papers), Gear and Bearing Dynamics Analysis (9 papers) and Structural Health Monitoring Techniques (8 papers). Dikang Peng collaborates with scholars based in China, Australia and Canada. Dikang Peng's co-authors include Zhongxiao Peng, Junchuan Shi, Dazhong Wu, Kai Goebel, Yibing Liu, Wei Teng, Xilin Li, Wei Teng, Xin Wu and Chris K. Mechefske and has published in prestigious journals such as Expert Systems with Applications, Mechanical Systems and Signal Processing and Reliability Engineering & System Safety.

In The Last Decade

Dikang Peng

14 papers receiving 332 citations

Hit Papers

align trajectories

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.

Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks

2021 206 citations Junchuan Shi, Dikang Peng et al. Mechanical Systems and Signal Processing profile →

Peers

Dikang Peng

CSE

ME

MM

CSE

AI

Chaoge Wang China

Renhe Yao China

Ali Dibaj Iran

Dongming Hou China

Dalian Yang China

Qiuyang Zhou China

Dong-Sik Gu South Korea

Mir Biuok Ehghaghi Iran

Zhongjun Yin China

Andreas Klausen Norway

Chaoge Wang China

Dikang Peng

311 ×1.1

CSE

217 ×1.3

ME

90 ×1.0

MM

40 ×0.8

CSE

39 ×1.2

AI

Citations per year, relative to Dikang Peng Dikang Peng (= 1×) peers Chaoge Wang

Countries citing papers authored by Dikang Peng

Since Specialization

Citations

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

Fields of papers citing papers by Dikang Peng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dikang Peng

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

All Works

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14 of 14 papers shown

1.

Li, Xilin, Wei Teng, Yangyang Zhang, Dikang Peng, & Yibing Liu. (2025). Dynamic normalized health indicator construction and Bayesian recurrent state estimation for remaining useful life prediction of high-speed bearings in wind turbine drivetrain. Measurement. 246. 116725–116725. 4 indexed citations

2.

Teng, Wei, et al.. (2025). Sparsity-assisted energy decoupling model for fault detection of planetary ring gear in wind turbines. Mechanical Systems and Signal Processing. 238. 113235–113235. 1 indexed citations

3.

Peng, Dikang, Wade A. Smith, Robert B. Randall, et al.. (2024). Iterative improvement in tacholess speed estimation using instantaneous error estimation for machine condition monitoring in variable speed. Mechanical Systems and Signal Processing. 216. 111488–111488. 4 indexed citations

4.

Teng, Wei, et al.. (2024). Trend-constrained pairing based incremental transfer learning for remaining useful life prediction of bearings in wind turbines. Expert Systems with Applications. 263. 125731–125731. 8 indexed citations

5.

Teng, Wei, et al.. (2024). Sparsity and Periodicity-Induced Symplectic Geometry Decomposition for Incipient Fault Diagnosis of Wind Turbine Gearbox. IEEE Transactions on Instrumentation and Measurement. 73. 1–12. 3 indexed citations

6.

Peng, Dikang, et al.. (2023). Use of generalized Gaussian cyclostationarity for blind deconvolution and its application to bearing fault diagnosis under non-Gaussian conditions. Mechanical Systems and Signal Processing. 196. 110351–110351. 28 indexed citations

7.

Li, Xilin, et al.. (2023). Feature fusion model based health indicator construction and self-constraint state-space estimator for remaining useful life prediction of bearings in wind turbines. Reliability Engineering & System Safety. 233. 109124–109124. 41 indexed citations

8.

Peng, Dikang, et al.. (2023). Cyclic band Box-Cox sparse measures based blind filtering and its application to bearing fault diagnosis. Measurement. 218. 113054–113054. 7 indexed citations

9.

Teng, Wei, et al.. (2023). A Multiperiodicity-Induced Sparse-Fidelity Representation Model for Compound Fault Diagnosis of Wind Turbine Gearbox. IEEE Transactions on Instrumentation and Measurement. 72. 1–12. 9 indexed citations

10.

Peng, Dikang, Wei Teng, & Yibing Liu. (2023). Improved Energy Spectrum via Spectral Correntropy-Based Coherence-Gram for Bearing Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement. 72. 1–11. 3 indexed citations

11.

Peng, Dikang, Yuejian Chen, Ming J. Zuo, & Chris K. Mechefske. (2023). Assessment and improvement of the accuracy of tacholess instantaneous speed estimation. Mechanical Systems and Signal Processing. 202. 110706–110706. 5 indexed citations

12.

Shi, Junchuan, et al.. (2021). Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks. Mechanical Systems and Signal Processing. 162. 107996–107996. 206 indexed citations breakdown →

13.

Peng, Dikang, Wade A. Smith, Robert B. Randall, Zhongxiao Peng, & Chris K. Mechefske. (2021). Speed estimation in planetary gearboxes: A method for reducing impulsive noise. Mechanical Systems and Signal Processing. 159. 107786–107786. 17 indexed citations

14.

Zhou, Xiaoqin, Xiuzhi He, Dikang Peng, Yixuan J. Hou, & Qiang Liu. (2020). A practical methodology for enhancement and detection of transient faults in a gearbox without prior fault feature information. Measurement Science and Technology. 32(3). 35116–35116. 5 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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