Systems and methods for estimating future risk of failure of a wind turbine component using machine learning

A system for estimating future risk of failure of a component of a wind turbine, the system comprising:

• a controller comprising at least one processor, the at least one processor configured to perform a plurality of operations, the plurality of operations comprising:
• receiving a plurality of different types of data associated with the wind turbine or a fleet of wind turbines, the plurality of different types of data comprising, at least, reliability data, the reliability data comprising, at least, time-to-event data from the wind turbine or the fleet of wind turbines;
• determining a number of failures or a number of suspensions present in the time-to-event data;
• comparing the number of failures or the number of suspensions to a threshold;
• generating a failure prediction model for the component based on the reliability data and available time-series measurements;
• applying the failure prediction model to the plurality of different types of data associated with the wind turbine or the fleet of wind turbines based on types of data available in the received plurality of different types of data, the applied failure prediction model comprising one of a conditional survival model or a joint conditional survival model;
• using the default model as the failure prediction model when the number of failures or the number of suspensions is below the threshold;
• estimating, via the failure prediction model, the future risk of failure of the wind turbine;
• and
• implementing a control action based on the future risk of failure, wherein implementing the control action comprises at least one of shutting down the industrial asset or shutting down the component of the industrial asset.