robust model- based fault detection and isolation for v47/660kw wind turbine

in this paper, in order to increase the efficiency, to reduce the cost and to prevent the failures of wind turbines, which lead to an extensive break down, a robust fault diagnosis system is proposed for v47/660kw wind turbine operated in manjil wind farm, gilan province, iran. according to the acquired data from iran wind turbine industry, common faults of the wind turbine such as sensor faults, actuator faults and component faults are identified and considered in fault detection and isolation (fdi) system design. various faults in abrupt and incipient natures can be detected and isolated using the indicators of faults, namely residuals, that are derived based on unknown input observer (uio) approach. moreover, some thresholds are exploited to evaluate the produced residuals. the robustness of the proposed method against parameter uncertainties is shown as well. simulations are performed in matlab/simulink environment to demonstrate the effectiveness of the proposed method using the actual parameters derived from the turbine model.