Wind Turbine Gearbox Diagnosis Based on Stator Current

Abstract

Early detection of faults in wind energy systems can reduce downtime, operating, and maintenance costs while increasing productivity. This paper proposes a method based on the analysis of generator stator current signals to detect faults in a wind turbine gearbox equipped with a doubly fed induction generator (DFIG). A localized parameter model was established to simulate the vibratory response of a two-stage gear system under healthy and faulty conditions. The simulation was performed in the MATLAB/Simulink environment. The results include a detailed analysis of the mechanical part of the gearbox, highlighting mesh stiffness, output speed, and accelerations. Additionally, the electrical part was evaluated based on the current supplied by the doubly fed induction generator. The results were presented in the case of healthy gears and in the presence of faults such as a broken or cracked tooth. Fast Fourier transform (FFT) analysis was employed to detect gear defects in the stator current signal. The presence of a crack or broken tooth in the gearbox induces modulation of the DFIG stator current signals according to the shaft frequencies corresponding to the faulty gear. These findings provide a preliminary basis for the detection and diagnosis of this type of failure.

Time-Frequency Fusion Features-Based GSWOA-KELM Model for Gear Fault Diagnosis

“…Gears are essential components to ensure the normal operation of various types of rotating machinery and are widely used in all kinds of industrial scenarios, such as wind turbines and automotive transmissions [1][2][3]. However, gear mesh surfaces are subjected to operating environments that result in poor lubrication, as evidenced by the mechanical impurities in oil, oil film disruption, etc., which further causes non-lubricating factors such as friction on the tooth surface, leading to surface deterioration, scuffing, and permanent deformation, etc.…”