Abstract
Fault of gearbox is one of the significant causes which lead to high cost of wind farm, so early fault prediction of gearbox is meaningful for ensuring reliable running and reducing maintenance costs. With condition monitoring data, the relation between gearbox temperature and potential faults was researched and a new method for online fault prediction of wind turbine gearbox was presented. First, the temperature prediction model for normal behavior of gearbox was built up by non-linear regression analysis. Then, a detecting function which can indicate the deviation between actual running state and prediction state of gearbox was introduced. The condition of gearbox could be monitored by comparing the real-time value of detecting function with the chosen threshold. Theoretical analysis and simulation results demonstrated that this method could predict the abnormality of gearbox in time, and it can be applied to monitor the running condition of gearbox.
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