Fault diagnosis of wind turbine gearbox using DFIG stator current analysis

Abstract

Gearbox faults are a leading reliability issue in wind turbines. Generator current-based methods have been successfully used in gearbox fault diagnosis and have shown advantages over the traditional vibration-based techniques in terms of implementation, cost, and reliability. This paper proposed a new generator stator current-based fault diagnostic method for the gearboxes in doubly-fed induction generator (DFIG)-based wind turbines under varying rotating speed conditions. Hilbert transform is first used to demodulate the stator current signal, and then a Vold-Kalman filter is designed to separate the nonstationary fault-related components (called the faulty signal) from the demodulated nonstationary stator current signal. Next, a synchronous resampling algorithm is designed to convert the nonstationary faulty signal to a stationary signal. Finally, the power spectral density (PSD) analysis is applied to the resampled faulty signal for the gearbox fault diagnosis. Experimental results obtained from a DFIG wind turbine drivetrain test rig are provided to verify the effectiveness of the proposed method for gearbox fault diagnosis.