Name
Title | ||
|---|---|---|
Universal Domain Adaptation in Fault Diagnostics With Hybrid Weighted Deep Adversarial Learning |
Abstract | ||
|---|---|---|
In the past years, the practical cross-domain machinery fault diagnosis problems have been attracting growing attention, where the training and testing data are collected from different operating conditions. The recent advances in closed-set domain adaptation have well addressed the basic problem where the fault mode sets are identical in the source and target domains. While some attempts have als... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TII.2021.3064377 | IEEE Transactions on Industrial Informatics |
Keywords | DocType | Volume |
Fault diagnosis,Feature extraction,Testing,Training,Machinery,Transfer learning,Informatics | Journal | 17 |
Issue | ISSN | Citations |
12 | 1551-3203 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |