Extracting spatially global and local attentive features for rolling bearing fault diagnosis in electrical machines using attention stream networks
Abstract A health diagnosis mechanism of rolling element bearings is necessary since the most frequent faults in rotating electrical machines occur in the bearing parts. Recently, convolutional neural networks (CNNs) have redefined the state‐of‐the‐art accuracy for bearing fault detection and identi...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-07-01
|
| Series: | IET Electric Power Applications |
| Online Access: | https://doi.org/10.1049/elp2.12063 |