Modeling and Optimizing the Composite Prepreg Tape Winding Process Based on Grey Relational Analysis Coupled with BP Neural Network and Bat Algorithm

Table 2 Experiment and measurement results

No.	Process parameters				Tensile strength (MPa)	S/N ratio	Void content (%)	S/N ratio
No.	T	F	P	V	Tensile strength (MPa)	S/N ratio	Void content (%)	S/N ratio
1	75	300	1000	15	896.92	59.0551	1.64	− 4.2969
2	50	300	2000	10	942.36	59.4843	1.19	− 1.5109
3	100	300	2000	10	1012.24	60.1057	0.25	12.0412
4	75	500	1500	15	951.33	59.5666	1.26	− 2.0074
5	75	300	1500	10	1210.68	61.6606	0.13	17.7211
6	75	300	2000	5	1123.47	61.0112	0.35	9.1186
7	100	500	1500	10	1062.27	60.5247	0.73	2.7335
8	50	500	1500	10	920.61	59.2815	1.45	− 3.2274
9	75	300	1500	10	1212.53	61.6739	0.15	16.4782
10	75	300	1500	10	1209.32	61.6508	0.17	15.3910
11	75	500	1000	10	1029.13	60.2494	1.39	− 2.8603
12	75	100	1500	5	967.14	59.7098	0.95	0.4455
13	75	500	2000	10	1018.74	60.1613	0.71	2.9748
14	100	100	1500	10	951.72	59.5702	0.87	1.2096
15	75	100	2000	10	866.58	58.7562	0.59	4.5830
16	75	300	1500	10	1213.24	61.6789	0.14	17.0774
17	75	300	1500	10	1215.31	61.6937	0.15	16.4782
18	100	300	1500	15	1130.29	61.0638	0.28	11.0568
19	50	100	1500	10	823.21	58.3102	0.79	2.0475
20	75	100	1500	15	876.68	58.8568	0.38	8.4043
21	75	100	1000	10	846.43	58.5518	1.68	− 4.5062
22	50	300	1500	5	1116.38	60.9562	0.31	10.1728
23	50	300	1500	15	783.26	57.8781	2.12	− 6.5267
24	75	300	2000	15	911.07	59.1910	1.16	− 1.2892
25	100	300	1500	5	1134.81	61.0985	0.27	11.3727
26	100	300	1000	10	997.85	59.9813	1.06	− 0.5061
27	75	500	1500	5	1053.11	60.4495	0.73	2.7335
28	50	300	1000	10	921.39	59.2889	2.19	− 6.8089
29	75	300	1000	5	1106.54	60.8793	0.79	2.0475