Prediction of Flank Wear during Turning of EN8 Steel with Cutting Force Signals Using a Deep Learning Approach

Table 2

The details of layers and parameters using the CAE model.

Section	No	Layer name	Filters × kernels	Activation function	Output size	Parameters
CE	1	Input layer	—	—	—	—
	2	1D convolution	64 × 2	Sigmoid	(None, 1, 64)	448
	3	Dropout	—	—	—	0
	4	1D convolution	32 × 2	Sigmoid	(None, 1, 32)	4128
CD	5	1D transposed convolution	32 × 2	Sigmoid	(None, 1, 32)	2082
	6	Dropout	—	—	—	0
	7	1D transposed convolution	64 × 2	Sigmoid	(None, 1, 64)	4160
	8	1D transposed convolution	1 × 2	Sigmoid	(None, 1, 1)	129
Reconstructed output	9	—	—	—	(None, 1, 1)	—
Total no. of parameters						10,945