Renhe Yao

432 total citations · 1 hit paper
19 papers, 326 citations indexed

About

Renhe Yao is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Renhe Yao has authored 19 papers receiving a total of 326 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Control and Systems Engineering, 17 papers in Mechanical Engineering and 3 papers in Mechanics of Materials. Recurrent topics in Renhe Yao's work include Machine Fault Diagnosis Techniques (19 papers), Gear and Bearing Dynamics Analysis (16 papers) and Fault Detection and Control Systems (11 papers). Renhe Yao is often cited by papers focused on Machine Fault Diagnosis Techniques (19 papers), Gear and Bearing Dynamics Analysis (16 papers) and Fault Detection and Control Systems (11 papers). Renhe Yao collaborates with scholars based in China, India and United States. Renhe Yao's co-authors include Hongkai Jiang, Yunpeng Liu, Tao Zeng, Xingqiu Li, Kaibo Wang, Qiao Yang, Yutong Dong, Chaoqiang Liu, Zhenghong Wu and Bin Hai and has published in prestigious journals such as Mechanical Systems and Signal Processing, Reliability Engineering & System Safety and IEEE Sensors Journal.

In The Last Decade

Renhe Yao

17 papers receiving 312 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.

Counterfactual-augmented few-shot contrastive learning for machinery intelligent fault diagnosis with limited samples

2024 55 citations Yunpeng Liu, Hongkai Jiang et al. Mechanical Systems and Signal Processing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Renhe Yao China	8	286	172	85	53	38	19	326
Dikang Peng China	7	284 1.0×	171 1.0×	89 1.0×	33 0.6×	50 1.3×	14	341
Chaoge Wang China	10	311 1.1×	217 1.3×	90 1.1×	39 0.7×	40 1.1×	47	403
Shuzhi Dong China	10	332 1.2×	193 1.1×	102 1.2×	63 1.2×	25 0.7×	13	387
Jianping Yan China	9	335 1.2×	198 1.2×	103 1.2×	64 1.2×	19 0.5×	23	423
Zhen Shi China	10	305 1.1×	170 1.0×	103 1.2×	68 1.3×	25 0.7×	24	401
Haizhou Huang China	7	239 0.8×	177 1.0×	78 0.9×	43 0.8×	23 0.6×	16	327
Kyumin Na South Korea	11	260 0.9×	189 1.1×	62 0.7×	47 0.9×	37 1.0×	13	347
Feiyu Lu China	11	239 0.8×	99 0.6×	62 0.7×	61 1.2×	18 0.5×	26	297
Dong-Sik Gu South Korea	6	304 1.1×	209 1.2×	92 1.1×	32 0.6×	55 1.4×	14	388
Ali Dibaj Iran	5	302 1.1×	208 1.2×	131 1.5×	32 0.6×	35 0.9×	8	358

Countries citing papers authored by Renhe Yao

Since Specialization

Citations

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

Fields of papers citing papers by Renhe Yao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Renhe Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Renhe Yao. A scholar is included among the top collaborators of Renhe Yao 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 Renhe Yao. Renhe Yao 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:

19 of 19 papers shown

Jiang, Wenxin, et al.. (2025). A weighted frequency domain energy operator spectral method based on soft thresholding fast iterative filtering for rolling bearing incipient fault feature extraction. Structural Health Monitoring. 1 indexed citations

Yao, Renhe, et al.. (2024). Deep discriminative sparse representation learning for machinery fault diagnosis. Engineering Applications of Artificial Intelligence. 135. 108836–108836. 6 indexed citations

Yao, Renhe, Hongkai Jiang, Yunpeng Liu, et al.. (2024). Deep Sparse Representation Classification for Aeroengine Inter-shaft Bearing Fault Diagnosis. 167–173. 2 indexed citations

Jiang, Hongkai, et al.. (2024). Energy bubble entropy guided symplectic geometry mode decomposition for rotating machinery incipient fault feature extraction. Measurement Science and Technology. 35(12). 125124–125124. 1 indexed citations

Yao, Renhe, et al.. (2024). A sensitive spectrum entropy-assisted Bayesian online anomaly inference method for bearing incipient degradation dynamic detection. ISA Transactions. 147. 453–471.

Niu, Maogui, Hongkai Jiang, & Renhe Yao. (2024). Adaptive multiscale wavelet-guided periodic sparse representation for bearing incipient fault feature extraction. Science China Technological Sciences. 67(11). 3585–3596.

Liu, Yunpeng, Hongkai Jiang, Renhe Yao, & Tao Zeng. (2024). Counterfactual-augmented few-shot contrastive learning for machinery intelligent fault diagnosis with limited samples. Mechanical Systems and Signal Processing. 216. 111507–111507. 55 indexed citations breakdown →

Dong, Yutong, et al.. (2023). Rolling bearing intelligent fault diagnosis towards variable speed and imbalanced samples using multiscale dynamic supervised contrast learning. Reliability Engineering & System Safety. 243. 109805–109805. 45 indexed citations

Jiang, Hongkai, et al.. (2023). Rolling bearing incipient fault feature extraction using impulse-enhanced sparse time-frequency representation. Measurement Science and Technology. 34(10). 105124–105124. 4 indexed citations

10.

Zhang, Sicheng, et al.. (2023). Optimal periodicity-enhanced group sparse for bearing incipient fault feature extraction. Measurement Science and Technology. 34(8). 85101–85101. 6 indexed citations

11.

Yao, Renhe, et al.. (2023). An Integrated Framework via Spectrum Sparsity Measure and Dynamic Alarm Thresholds for Online Fault Detection. IEEE Sensors Journal. 23(24). 30642–30651. 1 indexed citations

12.

Yao, Renhe, et al.. (2023). A framework via impulses-oriented Gini index and extreme value distribution for rolling bearing dynamic fault alarm and identification. Mechanism and Machine Theory. 189. 105437–105437. 6 indexed citations

13.

Liu, Yunpeng, et al.. (2023). Interpretable data-augmented adversarial variational autoencoder with sequential attention for imbalanced fault diagnosis. Journal of Manufacturing Systems. 71. 342–359. 42 indexed citations

14.

Yao, Renhe, et al.. (2022). An integrated framework via key-spectrum entropy and statistical properties for bearing dynamic health monitoring and performance degradation assessment. Mechanical Systems and Signal Processing. 187. 109955–109955. 46 indexed citations

15.

Yao, Renhe, et al.. (2022). Multiband weights-induced periodic sparse representation for bearing incipient fault diagnosis. ISA Transactions. 136. 483–502. 11 indexed citations

16.

Hai, Bin, et al.. (2021). Rolling bearing fault feature extraction using non-convex periodic group sparse method. Measurement Science and Technology. 32(10). 105005–105005. 11 indexed citations

17.

Yao, Renhe, Hongkai Jiang, Zhenghong Wu, & Kaibo Wang. (2021). Periodicity-enhanced sparse representation for rolling bearing incipient fault detection. ISA Transactions. 118. 219–237. 31 indexed citations

18.

Wang, Kaibo, Hongkai Jiang, Bin Hai, & Renhe Yao. (2021). Rolling bearing fault feature detection using nonconvex wavelet total variation. Measurement. 179. 109471–109471. 6 indexed citations

19.

Yao, Renhe, et al.. (2021). Bearing incipient fault feature extraction using adaptive period matching enhanced sparse representation. Mechanical Systems and Signal Processing. 166. 108467–108467. 52 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.

Explore authors with similar magnitude of impact