Wind turbine gearbox temperature prediction based on improved whale optimized long short-term memory network

Abstract

Aiming at the problem of low prediction accuracy of wind turbine gearbox temperature, the improved whale algorithm is used to optimize the long and short term memory network to predict the oil temperature of gearbox. The input data is based on the grey correlation degree to mine the parameters that are highly correlated with the oil temperature of the gear box, and the prediction model under healthy state is established. Finally, the experimental analysis shows that the method used in this paper has good accuracy in the oil temperature prediction of gearbox.