Baoping Tang

9.5k total citations · 4 hit papers
209 papers, 7.7k citations indexed

About

Baoping Tang is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Baoping Tang has authored 209 papers receiving a total of 7.7k indexed citations (citations by other indexed papers that have themselves been cited), including 166 papers in Control and Systems Engineering, 99 papers in Mechanical Engineering and 46 papers in Mechanics of Materials. Recurrent topics in Baoping Tang's work include Machine Fault Diagnosis Techniques (148 papers), Gear and Bearing Dynamics Analysis (79 papers) and Fault Detection and Control Systems (48 papers). Baoping Tang is often cited by papers focused on Machine Fault Diagnosis Techniques (148 papers), Gear and Bearing Dynamics Analysis (79 papers) and Fault Detection and Control Systems (48 papers). Baoping Tang collaborates with scholars based in China, United States and Singapore. Baoping Tang's co-authors include Minghang Zhao, Lei Deng, Michael Pecht, Yi Qin, Xuyun Fu, Shisheng Zhong, Tengwei Song, Yi Wang, Kai Zhang and Wenyi Liu and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Chemical Engineering Journal and IEEE Transactions on Industrial Electronics.

In The Last Decade

Baoping Tang

198 papers receiving 7.5k citations

Hit Papers

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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.

Deep Residual Shrinkage Networks for Fault Diagnosis

2019 994 citations Minghang Zhao, Baoping Tang et al. profile →
Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes

2017 312 citations Minghang Zhao, Baoping Tang et al. profile →
Condition monitoring of wind turbines based on spatio-temporal fusion of SCADA data by convolutional neural networks and gated recurrent units

2019 193 citations Baoping Tang, Lei Deng et al. profile →
Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction

2021 171 citations Yi Qin, Baoping Tang et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Baoping Tang	5.6k	3.4k	1.8k	940	864	209	7.7k
Yi Qin	4.6k 0.8×	3.1k 0.9×	1.3k 0.8×	597 0.6×	968 1.1×	266	7.2k
Jinglong Chen	5.4k 1.0×	3.0k 0.9×	1.6k 0.9×	590 0.6×	746 0.9×	188	7.1k
Minping Jia	4.9k 0.9×	3.2k 0.9×	1.6k 0.9×	571 0.6×	587 0.7×	154	6.8k
Jong-Myon Kim	3.9k 0.7×	2.8k 0.8×	1.4k 0.8×	1.2k 1.3×	913 1.1×	291	6.9k
Yanyang Zi	7.1k 1.3×	5.0k 1.5×	2.5k 1.4×	1.4k 1.5×	719 0.8×	177	9.2k
Chuang Sun	5.2k 0.9×	2.8k 0.8×	1.5k 0.9×	565 0.6×	669 0.8×	127	7.2k
Feng Jia	6.5k 1.2×	3.9k 1.1×	2.3k 1.3×	600 0.6×	607 0.7×	48	8.2k
Hongkai Jiang	6.8k 1.2×	4.1k 1.2×	2.3k 1.3×	489 0.5×	587 0.7×	132	8.0k
Zhibin Zhao	4.0k 0.7×	2.2k 0.6×	1.1k 0.6×	619 0.7×	913 1.1×	148	6.3k
Peter W. Tse	4.6k 0.8×	3.5k 1.0×	2.2k 1.3×	1.3k 1.4×	574 0.7×	166	7.2k

Countries citing papers authored by Baoping Tang

Since Specialization

Citations

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

Fields of papers citing papers by Baoping Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Baoping Tang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Yi, et al.. (2024). Multi-objective optimal deep deconvolution and its application to early fault signal enhancement of rotating machineries. Mechanical Systems and Signal Processing. 221. 111722–111722. 7 indexed citations

Tang, Baoping, et al.. (2024). A hybrid physics-corrected neural network for RUL prognosis under random missing data. Expert Systems with Applications. 256. 124939–124939. 3 indexed citations

Tang, Baoping, et al.. (2024). Simulation data-driven adaptive frequency filtering focal network for rolling bearing fault diagnosis. Engineering Applications of Artificial Intelligence. 138. 109371–109371. 6 indexed citations

Zhu, Peng, et al.. (2024). Digital twin-enabled entropy regularized wavelet attention domain adaptation network for gearboxes fault diagnosis without fault data. Advanced Engineering Informatics. 64. 103055–103055. 18 indexed citations

Tang, Baoping, et al.. (2024). WTFormer: RUL prediction method guided by trainable wavelet transform embedding and lagged penalty loss. Advanced Engineering Informatics. 62. 102710–102710. 5 indexed citations

Wang, Yi, et al.. (2024). A cross-session non-stationary attention-based motor imagery classification method with critic-free domain adaptation. Biomedical Signal Processing and Control. 100. 107122–107122. 1 indexed citations

Zhao, Chunhua, Baoping Tang, & Lei Deng. (2024). Missing-Measurements-Tolerant Compressed Sensing in Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Transactions on Instrumentation and Measurement. 73. 1–13. 4 indexed citations

Yu, Xiaoxia, Zhigang Zhang, Baoping Tang, & Minghang Zhao. (2024). Meta-Adaptive Graph Convolutional Networks With Few Samples for the Fault Diagnosis of Rotating Machinery. IEEE Sensors Journal. 24(12). 19237–19252. 1 indexed citations

Zhang, Guangyao, Yi Wang, Xiaomeng Li, Yi Qin, & Baoping Tang. (2023). Health indicator based on signal probability distribution measures for machinery condition monitoring. Mechanical Systems and Signal Processing. 198. 110460–110460. 32 indexed citations

10.

Wang, Yi, et al.. (2023). Slope synchronous chirplet transform and its application to tacho-less order tracking of rotating machineries. Mechanical Systems and Signal Processing. 196. 110357–110357. 20 indexed citations

11.

Wang, Yi, et al.. (2023). Physics-informed deep filtering of ultrasonic guided waves for incipient defect inspection of large-scale square tube structures. Journal of Sound and Vibration. 567. 118066–118066. 6 indexed citations

12.

Li, Feng, et al.. (2023). Variational eligibility trace meta-reinforcement recurrent network for residual life prediction of space rolling bearings. Applied Soft Computing. 145. 110582–110582. 2 indexed citations

13.

Wang, Yi, et al.. (2023). Correlation warping radius tracking for condition monitoring of rolling bearings under varying operating conditions. Mechanical Systems and Signal Processing. 208. 110943–110943. 5 indexed citations

14.

Tang, Baoping, et al.. (2023). An integrated network architecture for data repair and degradation trend prediction. Mechanical Systems and Signal Processing. 200. 110610–110610. 13 indexed citations

15.

Wang, Yi, et al.. (2023). Deep time–frequency learning for interpretable weak signal enhancement of rotating machineries. Engineering Applications of Artificial Intelligence. 124. 106598–106598. 12 indexed citations

16.

Chen, Fafa, et al.. (2020). Pattern recognition of a sensitive feature set based on the orthogonal neighborhood preserving embedding and adaboost_SVM algorithm for rolling bearing early fault diagnosis. Measurement Science and Technology. 31(10). 105007–105007. 41 indexed citations

17.

Chen, Fafa, Lili Liu, Baoping Tang, et al.. (2020). A novel fusion approach of deep convolution neural network with auto-encoder and its application in planetary gearbox fault diagnosis. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 235(1). 3–16. 13 indexed citations

18.

Tang, Baoping. (2011). Fault Diagnosis Model Based on Feature Compression with Orthogonal Locality Preserving Projection. Chinese Journal of Mechanical Engineering. 24(5). 891–891. 9 indexed citations

19.

Tang, Baoping. (2004). Research on mechanical measurement-oriented intelligent virtual controls. Chinese Journal of Mechanical Engineering. 17(3). 356–356. 1 indexed citations

20.

Tang, Baoping. (2003). Research of problems on realizing direct algorithm of wavelet transform. Chinese Journal of Mechanical Engineering. 16(2). 136–136. 1 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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