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Fault diagnosis of pitch sensor bias for wind turbine based on the multi-innovation Kalman filter

This paper presents a fault diagnosis method for detecting pitch sensor offset fault according to the mechanical structure characteristics of wind turbine. The method establishes corresponding relation between the change of pitch angle and the minute displacement which produced by the force acting on tower of wind turbine. It is based on the change of displacement to diagnosis whether the fault occurs. With regard to the large noise of sensors, we adopt the multi-innovation Kalman filter to enhance the estimation accuracy and convergence speed. The simulation results show that the multi-innovation Kalman filter based method can diagnose the fault effectively and is better than the common Kalman filter.