Name
Title | ||
|---|---|---|
Prior Knowledge-Augmented Self-Supervised Feature Learning for Few-Shot Intelligent Fault Diagnosis of Machines |
Abstract | ||
|---|---|---|
Data-driven intelligent diagnosis models expect to mine the health information of machines from massive monitoring data. However, the size of faulty monitoring data collected in engineering scenarios is limited, which leads to few-shot fault diagnosis as a valuable research point. Fortunately, it is possible to reduce the required amount of training data by integrating prior diagnosis knowledge in... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TIE.2022.3140403 | IEEE Transactions on Industrial Electronics |
Keywords | DocType | Volume |
Data models,Fault diagnosis,Training,Feature extraction,Knowledge engineering,Monitoring,Representation learning | Journal | 69 |
Issue | ISSN | Citations |
10 | 0278-0046 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tianci Zhang | 1 | 0 | 0.34 |
| Jinglong Chen | 2 | 3 | 3.08 |
| Shuilong He | 3 | 26 | 7.68 |
| Zitong Zhou | 4 | 18 | 5.08 |