Early Detection and Diagnosis of Wind Turbine Abnormal Conditions Using an Interpretable Supervised Variational Autoencoder Model
The operation and maintenance of wind turbines benefit from reliable information on the wind turbine condition. Data-driven models use data from the supervisory data acquisition system. In particular, great performance is reported for artificial intelligence models. However, the lack of interpretabi...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-06-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/16/12/4544 |