Fault detection of large scale wind turbine systems

Abstract

Fault diagnosis of large scale wind turbine systems has received much attention in the recent years. Effective fault prediction would allow for scheduled maintenance and for avoiding catastrophic failures. Thus the availability of wind turbines can be enhanced and the cost for maintenance can be reduced. In this paper, we consider the sensor and actuator fault detection issue for large scale wind turbine systems where individual pitch control is used for loads reduction. The faults considered in the paper are mainly the blade root bending moment sensor faults and blade pitch actuator faults. With the aid of a dynamical model of the wind turbine system, a so-called H ∞ /H − observer in the finite frequency range, is used to generate the residual for fault detection. The observer is designed to be sensitive to faults but unsensitive to the disturbances, such as the wind turbulence. When there is a detectable fault, the observer sends an alarm signal if the residual evaluation is larger than a predefined threshold. The effectiveness of the proposed approach is demonstrated by simulation results for several fault scenarios.