**2. Temporal Feature**

When BP neural networks process data, there is no interrelationship between the front and back inputs of the network. However, the vibration signal of a motor is a onedimensional time series, and the temporal relationship between each sampling point has an important impact on the performance of the diagnosis. A recurrent neural network introduces memory units to interconnect the neurons in this layer based on the ordinary neural network. The state of the hidden layer is related to the input at this moment and the state of the hidden layer at the previous moment. Therefore, the relationship of the time dimension can be extracted from the original vibration sequence by recurrent neural networks.
