Wind turbine gearbox ice sensing and condition monitoring for fault prognosis and diagnosis

The gearbox is seen as one of the most important assets of a wind turbine, so a major concern is how to keep it running smoothly to maximise its service time and reduce the cost. However, wind turbines are often located at remote locations where icing is possible and likely, e.g. high altitudes or cold regions. This challenges the wind turbine stability and causes a variety of problems. Furthermore, rapid expansion of wind energy, along with high operation and maintenance costs, all lead to the need for a condition monitoring system which can offer diagnostics of present condition and prognostics of future condition to improve the reliability of wind turbine and reduce the cost of unscheduled maintenances and unexpected failures. The proposed approach is demonstrated by using a Bayesian Belief Network and Dynamic Bayesian Network under LabVIEW and GeNIe respectively. The proposed procedure is applied on a wind turbine gearbox model to show its feasibility