Physics based methodology for wind turbine failure detection, diagnostics & prognostics

The prediction of the time to failure for components within a wind turbine is becoming more important as a consequence of enlargement of the wind turbines and placing them offshore. These developments bring higher replacement and downtime costs with it in case of failure. Current failure prediction models are data driven or based on statistics, however both approaches are not sufficient to predict the failure accurately. This paper focuses on the actual loads acting on the system by taking into account how the component will fail or in other words the physics of failure. A generic physics of failure based methodology has been proposed that gives a step-by-step plan in which forces and operational data are taken into account. The methodology is divided into three parts: detection, diagnostics and prognostics. In order to validate the physics based methodology, a case study has been set up for one component and failure. SCADA and CMS data from three operating wind turbines are used to complete the case study. In this way both SCADA and CMS data are used in one method, where usually either SCADA or CMS is used. The degradation pattern and prediction of the time to failure are obtained. The case study has been proven that the methodology is useful in practice and shows the high potential of using this approach.