Intelligent Recognition Method of Turning Tool Wear State Based on Information Fusion Technology and BP Neural Network

Table 2

Experimental parameters and collected data.

Serial numbers	Experimental parameters				Collected data
	Degrees of wear	Spindle speed (r/min)	Feed rate (mm/min)	Cutting depth (mm)	AE sensor (V)	Vibration sensor (V)
1	1	560	20	0.4	0.7522	0.1542
2	1	800	30	0.6	1.4141	0.1732
3	1	1120	40	0.8	2.0434	0.2119
4	1	1600	50	1.0	3.1657	0.2183
5	2	560	30	0.8	1.1045	0.3117
6	2	800	20	1.0	1.9643	0.2944
7	2	1120	50	0.4	1.7929	0.2357
8	2	1600	40	0.6	3.9895	0.2698
9	3	560	40	1.0	2.3615	0.4471
10	3	800	50	0.8	3.3478	0.3960
11	3	1120	20	0.6	4.4762	0.1940
12	3	1600	30	0.4	4.9327	0.2112
13	4	560	50	0.6	2.0609	1.2597
14	4	800	40	0.4	2.2999	0.6498
15	4	1120	30	1.0	4.0951	0.3535
16	4	1600	20	0.8	4.4076	0.6331