TC4钛合金材料铣削加工分析及参数优化

doi:10.13229/j.cnki.jdxbgxb.20220681

摘要/Abstract

摘要：

为探究加工TC4钛合金材料时铣削加工参数对铣削力及材料去除率的影响规律并寻求最佳参数组合，基于正交实验方法设计实验，采用四刃球头铣刀进行侧铣实验。以铣削速度、每齿进给量、铣削深度和铣削宽度为变量，以铣削力和材料去除率为评价指标，基于极差分析法，揭示加工参数对铣削力和材料去除率的影响规律。分别采用灰色关联分析法（GRA）和粒子群优化（PSO）算法进行参数优化，基于回归分析方法建立铣削力预测模型，为PSO做准备。最后，经过试验验证，对两种优化方法进行对比分析，并对预测模型进行验证。结果表明，本文所建立的预测模型可准确高效地对铣削力进行预测，PSO优化效果更好。

关键词: 机械制造, 钛合金, 铣削力, 材料去除率, 灰色关联分析, 粒子群优化

Abstract:

In order to investigate the influence of milling parameters on the milling force and material removal rate when machining TC4 titanium alloy material and to find the best combination of parameters， side milling experiments designed based on the orthogonal experimental method were carried out with a four-edged ball-ended milling cutter. Milling speed， feed per tooth， milling depth and milling width were chosen as variables， while milling force and material removal rate were selected as evaluation indicators. The influence laws of machining parameters on milling force and material removal rate， based on the range analysis method， were found out. The grey relational analysis （GRA） and particle swarm optimization （PSO） algorithms were adopted to optimize the milling parameters respectively， meanwhile a milling force prediction model was established based on the regression analysis method to prepare for the PSO. Finally， the two optimization methods were compared and analyzed and the prediction model was verified through the verification experiments. The results show that the prediction model established in this paper can accurately and efficiently predict the milling force， and the optimization effect of PSO is much better.

Key words: mechanical manufacture, titanium alloy, milling force, material removal rate, grey relational analysis, particle swarm optimization

中图分类号:

TH161

巩亚东,丁明祥,李响,田近民. TC4钛合金材料铣削加工分析及参数优化[J]. 吉林大学学报(工学版), 2024, 54(4): 917-925.

Ya-dong GONG,Ming-xiang DING,Xiang LI,Jin-min TIAN. Milling analysis and parameter optimization for TC4 titanium alloy material[J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(4): 917-925.

图/表 18

表1

图1

表2

实验因素水平"

水平	铣削速度 $v c / m · m i n - 1$	每齿进给量 $f z / m m · z - 1$	铣削深度 $a p / m m$	铣削宽度 $a e / m m$
1	60	0.01	2.5	0.25
2	80	0.02	5	0.50
3	100	0.03	7.5	0.75
4	120	0.04	10	1.00

表2

表3

正交实验设计实验结果"

实验编号	$v c$ / （m·min^-1）	$f z$ / （mm·z^-1）	$a p$ /mm	$a e$ /mm	F/N	MRR/（mm³·min^-1）
1	60	0.01	2.5	0.25	22.625	79.58
2	60	0.02	5	0.5	66.936	636.62
3	60	0.03	7.5	0.75	131.299	2148.59
4	60	0.04	10	1	196.573	5092.96
5	80	0.01	5	0.75	61.519	636.62
6	80	0.02	2.5	1	59.103	848.82
7	80	0.03	10	0.25	115.367	1273.24
8	80	0.04	7.5	0.5	120.821	2546.48
9	100	0.01	7.5	1	79.705	1591.55
10	100	0.02	10	0.75	121.917	3183.10
11	100	0.03	2.5	0.5	79.483	795.77
12	100	0.04	5	0.25	68.193	1061.03
13	120	0.01	10	0.5	70.012	1273.24
14	120	0.02	7.5	0.25	69.557	954.93
15	120	0.03	5	1	98.043	3819.72
16	120	0.04	2.5	0.75	82.287	1909.86

表3

表4

合力F的极差分析结果"

水平	$v c$	$f z$	$a p$	$a e$
1	104.36	58.47	60.87	68.94
2	89.20	79.38	73.67	84.31
3	87.32	106.05	100.35	99.26
4	79.97	116.97	125.97	108.36
Delta	24.38	58.50	65.09	39.42
排秩	4	2	1	3

表4

图 2

表5

材料去除率MRR的极差分析结果"

水平	$v c$	$f z$	$a p$	$a e$
1	1989.4	895.2	908.5	842.2
2	1326.3	1405.9	1538.5	1313.0
3	1657.9	2009.3	1810.4	1969.5
4	1989.4	2652.6	2705.6	2838.3
Delta	663.1	1757.3	1797.1	1996.1
排秩	4	3	2	1

表5

图 3

图4

表6

表7

GRC均值"

项目	F				MRR
项目	$v c$	$f z$	$a p$	$a e$	$v c$	$f z$	$a p$	$a e$
水平1	0.6406	0.4679	0.4762	0.5046	0.635	0.5187	0.5196	0.5143
水平2	0.5787	0.5445	0.5241	0.5615	0.5968	0.6017	0.6121	0.5946
水平3	0.5720	0.6376	0.6181	0.6144	0.638 8	0.6784	0.6630	0.6755
水平4	0.5459	0.6871	0.7187	0.6567	0.6780	0.7499	0.7539	0.7642
$R i j$	0.0947	0.2192	0.2425	0.1522	0.0812	0.2312	0.2343	0.2499
$∑ R i j$	0.7086				0.7966
$w k$	0.47				0.53

表7

表8

表 9

极差法衡量加权灰色关联度"

铣削参数	代号	均值加权灰色关联度				$Δ$	排序
铣削参数	代号	水平1	水平2	水平3	水平4	$Δ$	排序
$v c$	A	0.6376*	0.5883	0.6074	0.6159	0.0493	4
$f z$	B	0.4948	0.5748	0.6592	0.7204*	0.2256	2
$a p$	C	0.4992	0.5708	0.6419	0.7374*	0.2382	1
$a e$	D	0.5097	0.5790	0.6468	0.7137*	0.2040	3

表 9

图 5

图 6

表10

图 7

图8

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实验编号	信噪比（S/N）		归一化		GRC
实验编号	F	MRR	F	MRR	F	MRR
1	-27.091 77	38.016 08	0	0	0.333 33	0.333 33
2	-36.513 20	56.077 61	0.501 71	0.500 00	0.500 86	0.500 00
3	-42.365 23	66.643 07	0.813 34	0.792 48	0.728 16	0.706 69
4	-45.870 48	74.139 41	1	1	1.000 00	1.000 00
5	-35.780 19	56.077 61	0.462 67	0.500 00	0.482 01	0.500 00
6	-35.432 19	58.576 31	0.444 14	0.569 17	0.473 55	0.537 15
7	-41.241 63	62.098 21	0.753 51	0.666 66	0.669 80	0.600 00
8	-41.642 85	68.118 81	0.774 87	0.833 33	0.689 53	0.750 00
9	-38.029 71	64.036 41	0.582 47	0.720 32	0.544 94	0.641 29
10	-41.721 29	70.057 01	0.779 05	0.886 99	0.693 53	0.815 64
11	-38.005 49	58.015 75	0.581 17	0.553 65	0.544 17	0.528 35
12	-36.674 80	60.514 55	0.510 31	0.622 82	0.505 21	0.570 01
13	-36.903 45	62.098 21	0.522 49	0.666 66	0.511 50	0.600 00
14	-36.846 82	59.599 43	0.519 47	0.597 49	0.509 93	0.554 01
15	-39.828 33	71.640 63	0.678 24	0.930 83	0.608 45	0.878 47
16	-38.306 62	65.620 03	0.597 21	0.764 16	0.553 84	0.679 49

实验编号	WGRG	排序
1	0.333 33	16
2	0.500 40	14
3	0.716 78	5
4	1.000 00	1
5	0.491 54	15
6	0.507 26	13
7	0.632 80	6
8	0.721 58	4
9	0.596 00	8
10	0.758 25	2
11	0.535 78	11
12	0.539 55	10
13	0.558 41	9
14	0.533 29	12
15	0.751 56	3
16	0.620 44	7

项目	平方和	自由度	均方	F	显著性
总计	24 145.673	15
回归	24 124.905	13	1 855.762	178.721	0.006
残差	20.767	2	10.384

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