Research on Fault Diagnosis for Pitch Sensors of Wind Turbines

Abstract

Abstract: Considering the biased output fault of pitch sensors for wind turbines, a fault diagnosis method based on the multi-innovation kalman filter algorithm was proposed. The corresponding relationship between the change of the pitch angle and the tiny displacement produced by the force acting on the tower was established according to the mechanical structure characteristics of wind turbines. More accurate estimated value for the tiny displacement was achieved by using the multi-innovation kalman filter algorithm which had higher convergence speed and estimation accuracy to reduce the large noise of the output information generated by sensors. The fault could be detected and the value of the pitch sensor bias could be estimated through the change of the tiny displacement. The simulation results show that the proposed approach is able to diagnose the pitch sensor bias fault effectively.

Key words: wind turbine, pitch sensor, multi-innovation kalman filter, fault diagnosis

CLC Number:

TP391.9

Zhai Yanjie, Wu Dinghui, Li Yiyang, Ji Zhicheng. Research on Fault Diagnosis for Pitch Sensors of Wind Turbines[J]. Journal of System Simulation, 2015, 27(7): 1451-1457.

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