Electrical & Computer Engineering, Department of
Document Type
Article
Date of this Version
2012
Citation
D. Lu, X. Gong, and W. Qiao, “Current-based diagnosis for gear tooth breaks in wind turbine gearboxes,” in Proceedings of IEEE Energy Conversion Congress and Exposition 2012 (ECCE 2012), Raleigh, NC, USA, Sept. 15-20, 2012, pp. 3780-3786.
Abstract
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 twostage 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.
Comments
(First Prize of the 2012 Best Paper Awards of the IEEE IAS Renewable and Sustainable Energy Conversion Systems Committee).