Sensor Fault Diagnosis of Wind Turbines for Fault Tolerant

This paper aims at the blade root moment sensor fault detection and isolation issue. The underlying problem is crucial to the successful application of the individual pitch control system which plays a key role for reducing the blade loads of large offshore wind turbines. In this paper, a wind turbine model is built based on the closed loop identification technique, where the wind dynamics is included in the model. The fault detection issue are investigated based on the residual generated by Kalman filter. The additive faults and multiplicative faults are investigated respectively. For the additive fault case, the mean value change detection of the residual and the generalized likelihood ratio test are utilized respectively. On the other hand, the multiplicative fault is handled by the variance change detection of the residuals. The fault isolation issue is proceeded with the help of dual sensor redundancy. Simulation results show that the proposed approach can be successfully applied to the underlying issue.