Inventus Holdings, LLC

Huiyi Zhang

Carmine A Priore, Iii

Norman Jeffrey Hammitt

Joseph D Prusa

A system for monitoring a plurality of wind turbines can include a turbine categorizer, executing on one or more computing platforms that categorizes each of a plurality of wind turbines as being damaged or undamaged to form a list of potentially damaged wind turbines. The system can also include a damage evaluator executing on the one or more computing platforms that predicts a damage type and a stage for each wind turbine in the list of potentially damaged wind turbines. The system can further include an impact engine executing on the one or more computing platforms that assigns a repair window and a priority for each wind turbine in the list of potentially damaged wind turbines based on a respective predicted damage type and stage.

Wind turbine damage detection system using machine learning

Systems and methods to monitor a wind turbine azimuth drivetrain. Azimuth variation characteristics data are accumulated from wind turbines over a period of time. Clusters of values within the azimuth variation characteristics data are identified and a respective condition of the main drivetrain is associated with different clusters of values. After the associating, a measured set of azimuth variation characteristics data is received. A cluster corresponds to values in the measured set of azimuth variation characteristics data is determined and a condition associated with that cluster is determined to be a condition associated with the subject main drivetrain. That condition is then reported.

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Juno Beach, FL, United States of America

Huiyi Zhang