Current-based diagnosis for gear tooth breaks in wind turbine gearboxes

Gearbox faults constitute a significant portion of all faults and downtime in wind turbines (WTs). Current-based gearbox fault diagnosis has significant advantages over traditional vibration-based techniques in terms of cost, implementation, and reliability. This paper derives a mathematical model for a WT drive train consisting of a two-stage gearbox and a permanent magnet (PM) generator, from which the characteristic frequencies of gear tooth breaks in generator stator current frequency spectra are clearly identified. A adaptive signal resampling algorithm is proposed to convert the variable fault characteristic frequencies to constant values for WTs running at variable speeds. A fault detector is proposed for diagnosis of gear tooth breaks using statistical analysis on the fault signatures extracted from the stator current spectra. Experimental results on a real gearbox are provided to show the effectiveness of the proposed model and method for diagnosis of gear tooth breaks.