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Jan Helsen Figure1Faster Failure Detection in Wind Turbine Drive-Trains

Machine learning is finding its way into wind energy. It can be beneficial in many aspects of the wind industry value chain, ranging from the planning phase of new farms to operational optimisation during their service life. For the latter it has big potential. A turbine has many sensors that allow detailed monitoring of its operation and this operational data can be used as input for machine learning strategies. By tailoring maintenance strategies to the information coming from anomaly detection based on monitoring algorithms maintenance can be optimised and turbine uptime improved. In particular by using already available SCADA sensor data, optimisation potential can be realised rapidly.

By Prof. Jan Helsen and Ing. Pieter Jan Jordaens, OWI-lab, Belgium

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