Icing is a complex atmospheric phenomenon that causes airflow disruption and degrades aerodynamically the original performance of the wind turbine blades (WTBs). This is due to blade sensitivity to minor changes in the airfoil geometry. Aerodynamic distortions induced by ice decrease the lift-to-draft ratio and pitch moment, increase the airfoil weight, and adversely alter the effectiveness of position angle and velocity. Typically, wind turbines exposed to all-weather conditions are equipped with icing prevention systems (IPS). However at the present time, no ice-detection technique has been proven effective, and the implementation of new strategies that effectively detect and mitigate blade icing adverse effects are needed. In this work, a WTB ice-detection technique that consists of a numerical design tool using Matlab/Simulink models and non-uniform rational B-spline (NURBs) based metamodeling algorithms is examined. This is carried out in terms of the blade icing effects on turbine aerodynamic performance in accordance to condition-based maintenance (CBM) and prognostics health management (PHM) techniques.

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