Junyu Guo

1.3k citations
58 papers · 878 · 2 hit papers · h-index 19

Impact in

Papers in

Junyu Guo

49 papers receiving 863 citations

Hit Papers

A parallel deep neural network for intelligent fault diagnosis of drilling pumps 2024 · 60 citations
600+1Years since publication255075

Peers

Junyu Guo
Comparison fields: 5 of 110
  • Statistics, Probability and Uncertainty 125
  • Safety, Risk, Reliability and Quality 135
  • Software 49
  • Control and Systems Engineering 265
  • Mechanical Engineering 304
Replace Xiangdi Kong with:
Xiangdi Kong China
Cláudio M.N.A. Pereira Brazil
Yongbo Zhang China
Jichuan Kang China
Hong Pei China
Taotao Zhou China
Xingyu Zhao China
Alberto Pliego Marugán Spain
Liping Sun China
Junyu Guo relative to Xiangdi Kong China Xiangdi Kong's profile →
Citations per field
00.5×1.5×
Xiangdi Kong · 1×
Citations per year

Countries citing papers authored by Junyu Guo

Since Specialization
Citations

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

Fields of papers citing papers by Junyu Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Junyu Guo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Junyu Guo Line = papers co-authored together Junyu Guo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A hybrid prognosis scheme for rolling bearings based on a novel health indicator and nonlinear Wiener process
Hit paper breakdown →
202488
2 202370
3
A parallel deep neural network for intelligent fault diagnosis of drilling pumps
Hit paper breakdown →
202460
4 202259
5 202039
6 202337
7 202334
8 202333
9 202231
10 202130
11 201830
12 201827
13 201625
14 202323
15 200622
16 202421
17 202421
18 202019
19 202218
20 201918

About Junyu Guo

Junyu Guo is a scholar working on Mechanical Engineering, Control and Systems Engineering, Mechanics of Materials, Safety, Risk, Reliability and Quality and Statistics, Probability and Uncertainty, having authored 58 papers that have together received 878 indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (14 papers), Reliability and Maintenance Optimization (11 papers), Gear and Bearing Dynamics Analysis (9 papers), Risk and Safety Analysis (7 papers), Oil and Gas Production Techniques (6 papers), Engineering Diagnostics and Reliability (5 papers), Software Reliability and Analysis Research (5 papers) and Fatigue and fracture mechanics (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (125 citations), Safety, Risk, Reliability and Quality (135 citations), Software (49 citations), Control and Systems Engineering (265 citations) and Mechanical Engineering (304 citations). Junyu Guo has collaborated with scholars based in China, Portugal and United Kingdom. Frequent co-authors include He Li, Yulai Yang, Jiang Wang, Zhiyuan Wang, Hong‐Zhong Huang, Mohammad Yazdi, Cheng‐Geng Huang, Lin Wang, Hooi Siang Kang and Yan‐Feng Li. Their work appears in journals such as Reliability Engineering & System Safety, Quality and Reliability Engineering International, IEEE Access, Measurement Science and Technology and Energy.

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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