Hi everyone, I'm a fourth-year undergraduate student pursuing a Bachelor's in Artificial Intelligence and Machine Learning, and I'm planning to do my final-year project in the wind energy sector. The idea I'm currently exploring is building a hybrid digital twin for wind turbine predictive maintenance, where a physics-based simulator is combined with AI/ML models to detect anomalies, estimate component health, and eventually predict failures (e.g., gearbox, bearings, blades, etc.). So far, I've started looking into OpenFAST as the physics simulation engine and have been reading about SCADA data, condition monitoring, and predictive maintenance. My tentative architecture is to use OpenFAST for the physics-based model and build AI models on top for anomaly detection and Remaining Useful Life (RUL) estimation. However, I'm still in the early research phase and would really appreciate guidance from people working in this domain.…