航空钛合金高效插铣加工实验与多目标优化研究

李益兵; 王辉雄; 庄可佳

doi:10.13433/j.cnki.1003-8728.20200511

航空钛合金高效插铣加工实验与多目标优化研究

doi: 10.13433/j.cnki.1003-8728.20200511

武汉理工大学机电工程学院，武汉　430070

基金项目: 国家自然科学基金项目（51705385）与领域基金项目（61400020108）

详细信息

作者简介:
李益兵（1978−），教授，博士，研究方向为先进制造与智能优化、机械设备故障诊断，ahlyb@whut.edu.cn

通讯作者:
庄可佳，副教授，硕士生导师，博士， zhuangkj@whut.edu.cn

中图分类号: TG506.9
计量
- 文章访问数: 115
- HTML全文浏览量: 61
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2019-10-19
- 网络出版日期: 2023-02-16
- 刊出日期: 2022-12-05

Study on Multi-objective Optimization and High Efficiency Plunge Milling Experiment of Titanium Alloy for Aviation

School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430070, China

摘要

摘要: 钛合金整体叶盘是航空发动机的重要零部件，结构复杂，加工难度大。插铣加工因其轴向承受能力强和刚性大等特性，非常适合加工钛合金整体叶盘这类难加工、结构复杂的零部件。针对钛合金插铣加工效率的问题，采用响应曲面法设计插铣实验，建立切削力经验模型，以切削力和材料去除率为目标，采用NSGA-II算法进行多目标优化获得Pareto最优解。研究表明：切削力随主轴转速的增加而缓慢减小，随切削宽度、切削步距和每齿进给量的上升而增加；与实验初始参数组合相比，优化后的材料去除率提高了81.19%，而切削力减小了23.68%，达到了本研究的高效加工目标。
- 钛合金 /
- 插铣 /
- 响应曲面法 /
- 切削力 /
- 多目标优化
Abstract: Titanium alloy blisk is an important part in the aero-engine, which has complex structure and difficult machining. Plunge milling is very suitable for machining difficult-to-cut materials such as titanium alloys and complex components due to its strong axial bearing capacity and high rigidity. Aiming at the machining efficiency in plunge milling of titanium alloy, the plunge milling experiment is designed by using the response surface methodology, and an empirical model for cutting force is established. With the goal of cutting force and material removal rate, the NSGA-II is used for multi-objective optimization to obtain the Pareto optimal solution. The results show that the cutting force decreases slowly with the increasing of spindle speed, and increases with the increasing of cutting width, cutting step and feed per tooth. Comparing with the experimental initial parameter combination, the optimal material removal rate increased by 81.19%, and the cutting force reduced by 23.68%. The results show that the present method can achieve the goal of high efficiency machining.
- Titanium alloy /
- plunge milling /
- response surface method /
- cutting force /
- multiobjective optimization

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图 1 实验装置

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图 2 切削力信号局部放大图

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图 3 切削力预测值与实验值

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图 4 残差随实验编号分布的散点图

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图 5 残差的正态性检验图

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图 6 n和a_s对F_c的影响

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图 7 n和f_z对F_c的影响

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图 8 a_e和f_z对F_c的影响

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图 9 a_s和f_z对F_c的影响

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图 10 Pareto最优前沿

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表 1 TC4钛合金各元素的质量分数 %

Al	V	Fe	N	C	O	H	Ti
6.0	4.0	0.3	0.05	0.1	0.2	0.0125	余量

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表 2 切削参数的编码及水平

切削参数	编码水平
切削参数	−2	−1	0	1	2
n /（r·min⁻¹）	600	900	1200	1500	1800
a_e/mm	1.5	2.5	3.5	4.5	5.5
a_s/mm	3	4	5	6	7
f_z/（mm·z⁻¹）	0.03	0.06	0.09	0.12	0.15

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表 3 实验数据

试验编号	切削参数				响应
试验编号	n/ （r·min⁻¹）	a_e/ mm	a_s/ （mm）	f_z/ （mm·z⁻¹）	MRR/ （mm³·min⁻¹）	F_c/ N
1	900	2.5	4	0.06	1080	340.08
2	1500	2.5	4	0.06	1800	317.82
3	900	4.5	4	0.06	1944	639.48
4	1500	4.5	4	0.06	3240	544.98
5	900	2.5	6	0.06	1620	490.38
6	1500	2.5	6	0.06	2700	332.76
7	900	4.5	6	0.06	2916	788.16
8	1500	4.5	6	0.06	4860	651.30
9	900	2.5	4	0.12	2160	555.78
10	1500	2.5	4	0.12	3600	447.78
11	900	4.5	4	0.12	3888	939.72
12	1500	4.5	4	0.12	6480	830.52
13	900	2.5	6	0.12	3240	776.58
14	1500	2.5	6	0.12	5400	573.06
15	900	4.5	6	0.12	5832	1240.38
16	1500	4.5	6	0.12	9720	943.80
17	600	3.5	5	0.09	1890	843.84
18	1800	3.5	5	0.09	5670	549.84
19	1200	1.5	5	0.09	1620	314.88
20	1200	5.5	5	0.09	5940	1040.52
21	1200	3.5	3	0.09	2268	386.22
22	1200	3.5	7	0.09	5292	705.36
23	1200	3.5	5	0.03	1260	316.44
24	1200	3.5	5	0.15	6300	890.88
25	1200	3.5	5	0.09	3780	604.80
26	1200	3.5	5	0.09	3780	610.80
27	1200	3.5	5	0.09	3780	627.96
28	1200	3.5	5	0.09	3780	614.46
29	1200	3.5	5	0.09	3780	620.58
30	1200	3.5	5	0.09	3780	604.32

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表 4 方差分析表

参数	自由度	平方和	均方	F值	P值	p / %
模型	11	1534905	139537	269.07	<0.001	99.40
n	1	122771	122771	236.74	<0.001	7.95
a_e	1	733384	733384	1414.18	<0.001	47.49
a_s	1	137795	137795	265.71	<0.001	8.92
f_z	1	468034	468034	902.51	<0.001	30.31
n²	1	16054	16054	30.96	<0.001	1.40
a_e²	1	10279	10279	19.82	<0.001	0.67
a_s²	1	5346	5346	10.31	0.005	0.35
na_s	1	13261	13261	25.57	<0.001	0.86
nf_z	1	5855	5855	11.29	0.003	0.38
a_ef_z	1	13130	13130	25.32	<0.001	0.85
a_sf_z	1	7216	7216	13.91	0.002	0.48
误差	18	9335	519			0.6
合计	29	1544239				100
R²	0.9940	R_adj²	0.9903	R_pre²	0.9784

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表 5 预测的20个Pareto最优解

编号	n /（r·min⁻¹）	a_e/mm	a_s/mm	f_z/（mm·z⁻¹）	MRR/（mm³·min⁻¹）	F_c/N
1	1800	5.500	7	0.150	20790	1376.625
2	1047.753	1.500	3	0.030	282.893	49.022
3	1770.950	1.500	7	0.030	1115.699	101.609
4	1799.848	2.910	7	0.124	9086.183	595.178
5	1800	2.845	7	0.129	9221.248	602.860
6	1799.930	2.231	7	0.068	3836.536	279.059
7	1800	2.676	7	0.116	7831.853	521.824
8	1799.993	3.239	7	0.150	12244.670	776.658
9	1800	2.812	7	0.111	7900.077	525.778
10	1799.993	3.824	7	0.150	14453.69	912.992
11	1800	2.807	7	0.097	6874.440	465.791
12	1799.990	2.992	7	0.127	9569.469	623.365
13	1800	3.799	7	0.150	14361.77	907.047
14	1800	3.158	7	0.131	10395.610	672.116
15	1799.995	4.032	7	0.150	15239.270	964.629
16	1799.998	2.480	7	0.108	6771.806	459.840
17	1799.989	3.636	7	0.150	13741.820	867.632
18	1800	2.165	7	0.069	3746.181	273.670
19	1799.994	5.266	7	0.150	19906.570	1305.530
20	1800	5.313	7	0.150	20084.920	1319.708

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表 6 优化与实验中心点对比结果

编号	n	a_e	a_s	f_z	MRR	F_c	MRR增益/ %	F_c增益/ %
中心点	1200	3.500	5	0.090	3780	610.295	−	−
5	1800	2.845	7	0.129	9221.248	602.860	143.950	−1.220
6	1799.930	2.231	7	0.068	3836.536	279.059	1.500	−54.280
11	1800	2.807	7	0.097	6874.440	465.791	81.190	−23.680

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