Current-Based Mechanical Fault Detection for Direct-Drive Wind Turbines via Synchronous Sampling and Impulse Detection

Abstract

Online fault detection is an effective means to improve wind turbine reliability and performance and reduce wind turbine downtime and operating and maintenance costs. Current-based wind turbine fault detection techniques have received more and more attention in academia and industry due to their nonintrusive character and economic advantages. This paper presents a novel computationally efficient high-resolution wideband synchronous sampling algorithm for the mechanical fault detection of variable-speed direct-drive wind turbines (i.e., no gearbox) only using nonstationary generator stator current measurements. The proposed algorithm synchronously resamples the current signals such that the varying characteristic frequencies of the excitations generated by wind turbine faults in the current signals become constant values. An impulse detection algorithm is then proposed to detect the faults by identifying the excitations from the frequency spectra of the synchronously sampled stator current signals. Experimental studies are carried out to demonstrate the effectiveness of the proposed algorithms for the detection of rotor eccentricity and bearing faults of a direct-drive wind turbine operating in variable-speed conditions.