Daichao Wang

573 citations
17 papers · 429 · 1 hit paper · h-index 7

Impact in

Papers in

Daichao Wang

16 papers receiving 419 citations

Daichao Wang's Hit Papers

Intelligent Fault Diagnosis Method Based on Full 1-D Convolutional Generative Adversarial Network 2019 · 205 citations
2050+2+4Years since publication50100150200

Peers

Daichao Wang
Comparison fields: 5 of 51
  • Control and Systems Engineering 351
  • Mechanical Engineering 193
  • Mechanics of Materials 103
  • Medical Laboratory Technology 6
  • Industrial and Manufacturing Engineering 36
Replace Jianping Yan with:
Jianping Yan China
Diwang Ruan China
Jingyan Xia China
David Verstraete United States
Zhen Shi China
Zhiwu Shang China
Jorge Nei Brito Brazil
Alessandro Paolo Daga Italy
Daichao Wang relative to Jianping Yan China Jianping Yan's profile →
Citations per field
00.5×8.6×
Jianping Yan · 1×
Citations per year

Countries citing papers authored by Daichao Wang

Since Specialization
Citations

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

Fields of papers citing papers by Daichao Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Daichao Wang, 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 Daichao Wang Line = papers co-authored together Daichao Wang links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1
Intelligent Fault Diagnosis Method Based on Full 1-D Convolutional Generative Adversarial Network
Hit paper breakdown →
2019205
2 2019101
3 202146
4 202228
5 202212
6 20237
7 20247
8 20255
9 20255
10 20244
11 20173
12 20242
13 20251
14 20251
15 20251
16 20251
17 20210

About Daichao Wang

Daichao Wang is a scholar working on Control and Systems Engineering, Mechanical Engineering, Mechanics of Materials, Artificial Intelligence and Information Systems, having authored 17 papers that have together received 429 indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (12 papers), Fault Detection and Control Systems (8 papers), Gear and Bearing Dynamics Analysis (6 papers), Engineering Diagnostics and Reliability (5 papers), Industrial Vision Systems and Defect Detection (2 papers), Advanced Algorithms and Applications (2 papers), Advanced Measurement and Detection Methods (2 papers) and Advanced Decision-Making Techniques (2 papers). The work is most often cited by research in Control and Systems Engineering (351 citations), Mechanical Engineering (193 citations), Mechanics of Materials (103 citations), Medical Laboratory Technology (6 citations) and Industrial and Manufacturing Engineering (36 citations). Daichao Wang has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Yibin Li, Yan Song, Shengyao Gao, Lei Jia, Yanjun Liu, Tao Wen, Hui Li, Jian Xing, Yang Han and Yan Song. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, IEEE Sensors Journal, Advanced Engineering Informatics, Ocean Engineering and IEEE/ASME Transactions on Mechatronics.

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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