Name
Title | ||
|---|---|---|
A Fusion CWSMM-Based Framework for Rotating Machinery Fault Diagnosis Under Strong Interference and Imbalanced Case |
Abstract | ||
|---|---|---|
Vibration signals and infrared images have different advantages and characteristics. Although a few recent researches have explored their information fusion in rotating machinery fault diagnosis, they show limited performance when facing strong interference and imbalanced cases. Therefore, a fusion framework based on confidence weight support matrix machine (CWSMM) is proposed. In this framework, ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TII.2021.3125385 | IEEE Transactions on Industrial Informatics |
Keywords | DocType | Volume |
Vibrations,Fault diagnosis,Feature extraction,Machinery,Monitoring,Interference,Evidence theory | Journal | 18 |
Issue | ISSN | Citations |
8 | 1551-3203 | 1 |
PageRank | References | Authors |
0.36 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Li | 1 | 509 | 46.11 |
| Jian Cheng | 2 | 1327 | 115.72 |
| Haidong Shao | 3 | 63 | 10.49 |
| K. Liu | 4 | 104 | 9.93 |
| Baoping Cai | 5 | 1 | 0.36 |