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 ...
Abstract: This study presents an integrated framework combining 1D-CNN-LSTM-Autoencoder-based anomaly detection with identity authentication using machine learning classifiers. The 1D-CNN-LSTM ...