Abstract: In this paper, we propose an anomaly detection model based on Extended Isolation Forest and Denoising Autoencoder, which achieves unsupervised anomaly detection with good generalization ...
Abstract: Accurate and interpretable fault diagnosis of wind turbines (WTs) is critical for ensuring reliable and efficient operation. However, existing model-driven and data-driven approaches often ...
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