一种对中定位机构的设计及其优化分析

doi:10.16180/j.cnki.issn1007-7820.2021.01.003

Abstract

Abstract:

Display positioning fixture is the key equipment on the display assembly line, which plays an important role in realizing the automatic assembly of display. In this paper, a pair of centering positioning mechanisms for the crank slider is designed for the display positioning fixture. In order to improve the positioning accuracy and versatility of the fixture, the crank slider mechanism is optimized by the penalty function method, MATLAB is used to simulate it, and the key components are optimized by finite element method. The results show that the slider has a certain stroke in the process of clamping and positioning the components, and is affected by the length of the crank, the length of the connecting rod and the minimum transmission angle. When the length of the crank and the length of the connecting rod are 300 mm and 500 mm, respectively, the general performance of the mechanism is the best. Finally, the key components are optimized and analyzed by the finite element method, and the optimal results are obtained, so that the positioning accuracy of the centering positioning mechanism reaches 0.38 mm.

Key words: centered positioning mechanism, penalty function method, crank slider mechanism, optimization analysis, minimum transmission angle, finite element methods

CLC Number:

TP242.3

SAN Hongjun, LI Pengyu, CHEN Jiupeng, HU Qiongqiong, LI Qi, ZHANG Kaixiang, WANG Chen. A Design and Optimization Analysis of the Centered Positioning Mechanism[J].Electronic Science and Technology, 2021, 34(1): 10-16.

Figures/Tables 15

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Table 1

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

Table 2

Figure 10.

Table 3

Figure 11.

Table 4

References 15

[1]	赵永强, 李瑞超, 侯红玲, 等. 磨床自定心中心架复位机构的设计与仿真[J]. 机械传动, 2019,43(7):111-115.
	Zhao Yongqiang, Li Ruichao, Hou Hongling, et al. Design and simulation of reset mechanism of self-centering center rest for grinding machine[J]. Journal of Mechanical Transmission, 2019,43(7):111-115.
[2]	邓援超, 张立, 杨超, 等. 机械锁紧装置中凸轮机构分析及优化设计[J]. 华侨大学学报(自然科学版), 2019,40(3):298-304.
	Deng Yuanchao, Zhang Li, Yang Chao, et al. Analysis and optimum design of cam mechanism in mechanical locking device[J]. Journal of Huaqiao University(Natural Science), 2019,40(3):298-304.
[3]	周跃鹏, 陈树人, 唐忠, 等. 曲柄滑块秸秆压缩机构振动研究-基于惯性力平衡法[J]. 农机化研究, 2019,41(4):37-41.
	Zhou Yuepeng, Chen Shuren, Tang Zhong, et al. Vibrationresearch of crank slidermechanismofstraw compression[J]. Journal ofAgricultural Mechanization Research, 2019,41(4):37-41.
[4]	王海涛, 丁玲龙, 王庆霞. 高速纺纱锭子两支撑孔加工专用夹具设计与分析[J]. 机械制造, 2013,51(11):79-82.
	Wang Haitao, Ding Linglong, Wang Qingxia. Design and analysis of special fixture for machining two supporting holes of high-speed spinning spindle[J]. Machinery, 2013,51(11):79-82.
[5]	顾岩秀, 华云松. 双足载人机器人的结构设计及高度优化[J]. 电子科技, 2016,29(2):77-80.
	Gu Yanxiu, Hua Yunsong. Structuraldesign and height optimization of manned biped robot[J]. Electronic Science and Technology, 2016,29(2):77-80.
[6]	董宁, 王宇平. 求解约束优化问题的引导多目标差分进化算法[J]. 吉林大学学报(工学版), 2015,45(2):569-575.
	Dong Ning, Wang Yuping. Guiding multi-objective differential evolution algorithm for constraint optimization[J]. Journal of Jilin University(Engineering and Technology Edition), 2015,45(2):569-575.
[7]	王训训, 陈天, 刘正杰, 等. 粒子群优化融合随机森林的电机故障诊断方法[J]. 微特电机, 2019,47(10):42-45.
	Wang Xunxun, Chen Tian, Liu Zhengjie, et al. Motorfault diagnosis method based on particle swarm optimization and random forest[J]. Smalland Special Electrical Machines, 2019,47(10):42-45.
[8]	张利凤, 胡小兵. 求解非线性约束问题的混合粒子群优化算法[J]. 计算机科学, 2011,38(S1):178-180.
	Zhang Lifeng, Hu Xiaobing. Hybrid particle swarm algorithm of solving nonlinear constraint optimization problems[J]. Computer Science, 2011,38(S1):178-180.
[9]	陈明方, 张凯翔, 陈久朋, 等. 基于MATLAB Robotics Toolbox的四足机器人轨迹仿真与优化[J]. 电子科技, 2020,33(9):31-37.
	Chen Mingfang, Zhang Kaixiang, Chen Jiupeng, et al. Simulation and optimization of quadruped robot trajectory based on MATLAB robotics toolbox[J]. Electronic Science and Technology, 2020,33(9):31-37.
[10]	Mazhoud I, Hadj-Hamou K, Bigeon J, et al. Particle swarm optimization for solvingengineering problems: A new constraint-handing mechanism[J]. Engineering Applicalions of Artificial Intelligence, 2013,26(4):1263-1273.
[11]	Elsayed S M, Sarker R A, Mezura-Montes E. Self-adaptive mix of particle swarm methodologies for constrained optimization[J]. Information Science, 2014,27(7):216-233.
[12]	钱学毅, 迟建华, 吴双. 基于微分进化算法的非对称弧齿锥齿轮约束多目标优化[J]. 图学学报, 2014,35(1):26-30.
	Qian Xueyi, Chi Jianhua, Wu Shuang. Asymmetricspiral bevel bears'constrainedmulti-objective optimization based on the differential evolutionary algorithm[J]. Journal of Graphics, 2014,35(1):26-30.
[13]	Lozano G G, Tiwari A, Turner C. A design algorithm to model fibre paths for manufacturing of structurally optimised composite laminates[J]. Composite Structures, 2018,20(4):822-895.
[14]	Beltramo T, Ranzan C, Hinrichs J, et al. Artificial neural network prediction of the biogas flow rate optimised with an ant colony algorithm[J]. Biosystems Engineering, 2016,14(3):68-78.
[15]	刘衍民. 一种求解约束优化问题的混合粒子群算法[J]. 清华大学学报(自然科学版), 2013,53(2):242-246.
	Liu Yanmin. Hybrid particleswarm optimizerforconstraint optimization problems[J]. Journal of Tsinghua University(Natural Science), 2013,53(2):242-246.

γ_min	最优解X^*		L₁	L₂	S_max
γ_min	a	b	L₁	L₂	S_max
40°	300	500	331.963 9	754.851 0	422.887 1
45°	300	500	357.589 1	743.054 5	385.465 4
50°	300	500	383.614 4	729.958 9	346.344 5
55°	300	500	409.780 4	715.597 7	305.817 2
60°	300	500	435.889 9	700.000 0	264.110 1

编号	x(H₁)	y(V₂)	z(FD₁)	变形量
1	1 125	380	10	3.490 5
2	1 050	380	10	3.108 8
3	1 200	380	10	4.128 9
4	1 125	380	7	10.317 0
5	1 125	380	13	1.579 1
6	1 125	342	10	4.788 2
?	?	?	?	?
12	1 064	410.9	7.560 9	6.726 7
13	1 186	410.9	7.560 9	8.487 2
14	1 064	410.9	12.439 0	1.495 5
15	1 186	410.9	12.439 0	1.884 9

待选点	x/mm	y/mm	z/mm	应力/MPa	变形量/mm
1	1 123.6	380	12.7	34.774	1.697
2	1 050	418	13	36.711	1.238

编号	x(H₁)	y(V₂)	z(FD₁)	变形量
1	1061.3	383.63	12.28	0.380 91
2	1070.3	379.19	11.16	0.395 86

A Design and Optimization Analysis of the Centered Positioning Mechanism

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 15

References 15

Related Articles 1

Metrics

Comments

Recommended 10