The purpose of this paper is to present the application of interval Linear Parameter Varying (LPV) identification and fault diagnosis approaches to a real wind turbine. Since wind turbines are highly non-linear systems when operating in their whole range of operation, a LPV model is used. Real field data and system identification techniques are used to identify the nominal model as well as its uncertainty. Fault detection is based on interval LPV observers that are used to generate an adaptive threshold to enhance the robustness of the fault detection test. Finally, fault isolation is based on an algorithmthat uses the residual fault sensitivity. Several fault scenarios are used to show the performance of the proposed approach.