Development of Deep Convolutional Neural Network with Adaptive Batch Normalization Algorithm for Bearing Fault Diagnosis

Table 1

Structural parameters of the WFK-CNN.

Number	Network layer	Convolution kernel size (step)	Number of convolution kernels	Output size (scale × depth)	Supplement
1	Convolution 1	64 × 1/16 × 1	16	128 × 16	Y
2	Pooling 1	2 × 1/2 × 1	16	64 × 16	N
3	Convolution 2	3 × 1/1 × 1	32	64 × 32	Y
4	Pooling 2	2 × 1/2 × 1	64	32 × 32	N
5	Convolution 3	3 × 1/1 × 1	64	32 × 64	Y
6	Pooling 3	2 × 1/2 × 1	64	16 × 64	N
7	Convolution 4	3 × 1/1 × 1	64	16 × 64	Y
8	Pooling 4	2 × 1/2 × 1	64	8 × 64	N
9	Convolution 5	3 × 1/1 × 1	64	6 × 64	N
10	Pooling 5	2 × 1/2 × 1	64	3 × 64	N
11	Full connection	100	1	100 × 1
12	Softmax	10	1	10