Rongzhen Zhao

641 total citations
39 papers, 489 citations indexed

About

Rongzhen Zhao is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Rongzhen Zhao has authored 39 papers receiving a total of 489 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Control and Systems Engineering, 12 papers in Mechanical Engineering and 11 papers in Mechanics of Materials. Recurrent topics in Rongzhen Zhao's work include Machine Fault Diagnosis Techniques (22 papers), Engineering Diagnostics and Reliability (11 papers) and Gear and Bearing Dynamics Analysis (10 papers). Rongzhen Zhao is often cited by papers focused on Machine Fault Diagnosis Techniques (22 papers), Engineering Diagnostics and Reliability (11 papers) and Gear and Bearing Dynamics Analysis (10 papers). Rongzhen Zhao collaborates with scholars based in China and United States. Rongzhen Zhao's co-authors include Linfeng Deng, Pengfei Chen, Yuqiao Zheng, Qiang He, Hongru Ma, Yunfeng Wen, Aihua Zhang, Wuyin Jin, Mingkuan Shi and Chuangxin Guo and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Neural Networks.

In The Last Decade

Rongzhen Zhao

36 papers receiving 472 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rongzhen Zhao China	14	361	220	115	77	64	39	489
Jiande Wu China	13	419 1.2×	306 1.4×	136 1.2×	68 0.9×	50 0.8×	90	604
Biliang Lu China	11	368 1.0×	194 0.9×	103 0.9×	104 1.4×	35 0.5×	18	473
Lixiao Cao China	14	440 1.2×	243 1.1×	129 1.1×	83 1.1×	47 0.7×	23	550
Shanshan Ji China	10	469 1.3×	292 1.3×	146 1.3×	87 1.1×	53 0.8×	20	640
Lizhi Liu China	7	496 1.4×	295 1.3×	184 1.6×	92 1.2×	59 0.9×	13	656
Prasanna Tamilselvan United States	7	427 1.2×	218 1.0×	139 1.2×	83 1.1×	80 1.3×	14	608
Baoqing Ding China	8	323 0.9×	175 0.8×	99 0.9×	50 0.6×	38 0.6×	24	423
Wenbin Huang China	12	285 0.8×	183 0.8×	106 0.9×	47 0.6×	71 1.1×	29	432
Tauheed Mian India	9	387 1.1×	263 1.2×	194 1.7×	43 0.6×	66 1.0×	16	534
Mohd Syahril Ramadhan Mohd Saufi Malaysia	8	455 1.3×	267 1.2×	128 1.1×	87 1.1×	48 0.8×	22	584

Countries citing papers authored by Rongzhen Zhao

Since Specialization

Citations

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

Fields of papers citing papers by Rongzhen Zhao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rongzhen Zhao

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

All Works

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20 of 20 papers shown

Zhao, Rongzhen, et al.. (2025). Multi-source contrastive cluster center method for cross-domain bearing fault identification. Engineering Applications of Artificial Intelligence. 161. 112056–112056. 1 indexed citations

Zhao, Rongzhen, et al.. (2025). Dimensionality reduction of rolling bearing fault data based on graph-embedded semi-supervised deep auto-encoders. Engineering Applications of Artificial Intelligence. 152. 110689–110689. 1 indexed citations

Chen, Pengfei, et al.. (2023). A novel bearing fault diagnosis method based joint attention adversarial domain adaptation. Reliability Engineering & System Safety. 237. 109345–109345. 50 indexed citations

Wu, Zhenzhi, Jing Zhang, Rongzhen Zhao, et al.. (2023). BIDL: a brain-inspired deep learning framework for spatiotemporal processing. Frontiers in Neuroscience. 17. 1213720–1213720.

Chen, Pengfei, et al.. (2023). Unsupervised structure subdomain adaptation based the Contrastive Cluster Center for bearing fault diagnosis. Engineering Applications of Artificial Intelligence. 122. 106141–106141. 15 indexed citations

Wu, Zhenzhi, et al.. (2022). Modeling learnable electrical synapse for high precision spatio-temporal recognition. Neural Networks. 149. 184–194. 6 indexed citations

Zhao, Rongzhen, et al.. (2022). Unsupervised domain adaptation of bearing fault diagnosis based on Join Sliced Wasserstein Distance. ISA Transactions. 129(Pt A). 504–519. 72 indexed citations

Liu, Jun, et al.. (2022). A New Fault Diagnosis Method for Unbalanced Data Based on 1DCNN and L2-SVM. Applied Sciences. 12(19). 9880–9880. 16 indexed citations

Zhao, Rongzhen, et al.. (2021). Structure Design and Analysis of Canted‐Cosine‐Theta (CCT) Superconducting Quadrupole Magnet. Shock and Vibration. 2021(1). 3 indexed citations

10.

Zhao, Rongzhen, et al.. (2021). A new method of vibration signal denoising based on improved wavelet. Journal of low frequency noise, vibration and active control. 41(2). 637–645. 6 indexed citations

11.

Zhao, Rongzhen, et al.. (2020). Rolling Bearing Fault Diagnosis Using a Deep Convolutional Autoencoding Network and Improved Gustafson–Kessel Clustering. Shock and Vibration. 2020. 1–17. 7 indexed citations

12.

Zhao, Rongzhen, et al.. (2020). A New Fault Diagnosis Method for Rotating Machinery Based on SCA-FastICA. Mathematical Problems in Engineering. 2020. 1–12. 14 indexed citations

13.

Zhao, Rongzhen, et al.. (2020). A new fault feature extraction method of rotating machinery based on finite sample function. Noise & Vibration Worldwide. 52(6). 137–144. 1 indexed citations

14.

Wen, Yunfeng, et al.. (2020). Data‐driven transient frequency stability assessment: A deep learning method with combined estimation‐correction framework. SHILAP Revista de lepidopterología. 1(3). 198–209. 21 indexed citations

15.

Zhao, Rongzhen, et al.. (2020). A New Fault Feature Extraction Method for Rotating Machinery Based on Multiple Sensors. Sensors. 20(6). 1713–1713. 8 indexed citations

16.

Zhao, Rongzhen, et al.. (2019). Deep Learning for Predicting the Operation of Under-Frequency Load Shedding Systems. 4142–4147. 5 indexed citations

17.

Zhao, Rongzhen, et al.. (2017). Fault diagnosis model based on NRS and EEMD for rolling-element bearing. 1–5. 2 indexed citations

18.

Zheng, Yuqiao & Rongzhen Zhao. (2015). Characteristics for wind energy and wind turbines by considering vertical wind shear. Journal of Central South University. 22(6). 2393–2398. 9 indexed citations

19.

Deng, Linfeng & Rongzhen Zhao. (2014). An improved spline-local mean decomposition and its application to vibration analysis of rotating machinery with rub-impact fault. Journal of Vibroengineering. 16(1). 414–433. 18 indexed citations

20.

Deng, Linfeng & Rongzhen Zhao. (2014). Fault feature extraction of a rotor system based on local mean decomposition and Teager energy kurtosis. Journal of Mechanical Science and Technology. 28(4). 1161–1169. 29 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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