ABSTRACT
In this chapter, a bearing fault diagnosis method based on convolutional recurrent neural network is proposed, which well combines the two classic deep learning models of convolution neural network and recurrent neural network to form a unified fault diagnosis network model with feature extraction and fault classification capabilities. The experimental results show that the proposed method can realize bearing fault classification under multiple working conditions, and the fault diagnosis accuracy is higher than that of conventional deep learning methods.
