Wind Turbine Fault Identification in Sample Imbalance Scenarios Using FRBCS With GAN Oversampling and Metric Learning
The operation data from different wind turbines (WTs) is not universal, due to the influence of installation, location, and environmental conditions, which caused incomplete and imbalanced fault sample data, and influenced the fault identification accuracy. Therefore, this paper proposes a fuzzy rul...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10815943/ |
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