Current-Based Gear Fault Detection for Wind Turbine Gearboxes

Abstract

Gearbox faults contribute to a significant portion of the faults and downtime of wind turbines. Gearbox fault detection using the electrical signals acquired from generator terminals has advantages over traditional vibration-based methods in terms of cost, hardware complexity, implementation, and reliability. This paper analyzes the principle of using the nonstationary stator current signals of a generator for the fault detection of a multistage gearbox connected to the generator in varying-speed conditions. Based on the analysis, the characteristic frequencies of various gearbox faults in the frequency spectra of the generator stator currents are identified. A method is then proposed for the fault detection of the gearbox using the current signals. The method consists of an adaptive signal resampling algorithm to convert the nonstationary characteristic frequencies of gearbox faults in the current signals to constant values when the gearbox operates in varying-speed conditions, a statistical analysis algorithm to extract the fault features from the frequency spectra of the resampled stator current signals, and two fault detectors based on the extracted fault features. Experimental results on a two-stage gearbox connected to an electric generator are given to show the effectiveness of the proposed analysis and method for detection of a variety of gear faults in the gearbox.