Vibration Images-Driven Fault Diagnosis Based on CNN and Transfer Learning of Rolling Bearing under Strong Noise

Table 1

CNN model parameters preset.

Items	Parameters
Batch size	24
Convolution1 kernel	Lengthwidthnumber = 556, stride = 1
Convolution2 kernel	Lengthwidthnumber = 5516, stride = 2
Convolution3 kernel	Lengthwidthnumber = 55120
Pool1 set	Type = max pooling, lengthwidth = 44, stride = 4
Pool2 set	Type = max pooling, lengthwidth = 66, stride = 6
Activate function	Relu
Loss function	Cross entropy
Optimizer	Stochastic gradient descent
Initial learning rate	0.001
Regularization	None