Fault detection and isolation of a real wind turbine using LPV observers

Abstract

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