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...
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| Published in: | Energies (Basel) Vol. 16; no. 12; p. 4544 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Basel
MDPI AG
01.06.2023
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| Subjects: | |
| ISSN: | 1996-1073, 1996-1073 |
| Online Access: | Get full text |
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