The focus of the paper is on a design of a fatigue load estimator for predictive condition monitoring systems (CMS) of wind turbines. In order to avoid high-price measurement equipment required for direct load measuring, an indirect approach is suggested using only measurements from supervisory control and data acquisition (SCADA) system. Estimated loads can be further used for prediction of remaining operating lifetime of turbine components, detection of high stress level or fault detection. An augmented Kalman filter is chosen as the fatigue load estimator because its characteristics well suit for the real time application. This paper presents results of the estimation of the gearbox fatigue load, often called shaft torque, using simulated data of wind turbine. Noise sensitivity of the algorithm is investigated by assuming different levels of measurement noise. Shaft torque estimations are compared with simulated data and as the obtained results are promising, further work will be on a validation of the method using real wind turbine data.
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