A condition monitoring method of wind turbine main bearings was proposed based on DBN.To reduce the modeling difficulties and decrease the training time,a correlation coefficient method was firstly applied to select the modeling variables.Further,a DBN temperature model of the normal behaviors of the main bearings was established and the main bearing temperature was predicted.This model overcomes the shortcomings of traditional neural network that randomly initializes the network weights and easily to fall ...