Wind turbines operate in harsh and variable environments, which can lead to wear and tear on their components over time. Traditional methods of turbine maintenance, such as periodic inspections or rule-based systems, can be time-consuming and may not identify all potential issues.

AI and machine learning (ML) can play a key role in condition monitoring of wind turbines in the wind energy industry. By training an ML model on data from turbine sensors, our solution can detect potential issues and diagnose them before they become major problems. In addition, ML models can be used to predict remaining useful life (RUL) of turbine components, enabling wind energy companies to schedule maintenance proactively and reduce downtime.