大型壁板自动钻铆定位误差分析与优化

doi:10.7527/S1000-6893.2015.0221

材料工程与机械制造

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

大型壁板自动钻铆定位误差分析与优化

齐振超¹, 张开富¹, 李原¹, 程晖²

1. 西北工业大学现代设计与集成制造技术教育部重点实验室, 西安 710072;
2. 西北工业大学机电学院, 西安 710072

收稿日期:2015-06-09 修回日期:2015-08-05 出版日期:2015-10-15 发布日期:2015-08-07
通讯作者: 张开富, Tel.: 029-88460773 E-mail: zhangkf@nwpu.edu.cn E-mail:zhangkf@nwpu.edu.cn
作者简介:齐振超男, 博士研究生。主要研究方向: 先进连接技术与装备。 Tel: 029-88460773 E-mail: qizhenchao2007@foxmail.com;张开富男, 博士, 教授, 博士生导师。主要研究方向: 数字化装配技术、复合材料加工技术。 Tel: 029-88460773 E-mail: zhangkf@nwpu.edu.cn
基金资助:
国家自然科学基金 (51305352)

Analysis and optimization for locating errors of large wing panel during automatic drilling and riveting

QI Zhenchao¹, ZHANG Kaifu¹, LI Yuan¹, CHENG Hui²

1. The Key Lab of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, Xi'an 710072, China;
2. School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China

Received:2015-06-09 Revised:2015-08-05 Online:2015-10-15 Published:2015-08-07
Supported by:
National Natural Science Foundation of China (51305352)

摘要/Abstract

摘要：

在机翼大型壁板自动钻铆工艺中,由于定位误差较大,壁板实际位姿和理论数模位姿之间难以建立精确的映射关系,而现有补偿工艺流程复杂,导致装配效率较低。着眼于工装设计补偿,针对大型壁板自动钻铆定位误差控制问题展开定位误差溯源分析和定位点布局优化。首先,根据自动钻铆工艺流程进行定位误差溯源,分析其误差的来源及传递机理;其次,将定位误差分为刚性误差和柔性误差两部分,采用Monte-Carlo法模拟刚性定位误差的分布,通过齐次坐标变换分析刚性误差的传递过程,利用有限元虚拟仿真计算关键特征点的柔性变形误差;再次,集成刚性误差与柔性误差,基于统计学思想讨论特定置信度下的定位误差分布规律;然后,基于脚本语言开发Abaqus参数化模型,通过Isight进行后台调用及赋值规划,实现基于带精英策略的非支配解排序遗传算法(NSGA-II)的定位点布局多目标优化;最后,以某型飞机机翼上侧壁板的一号组件为实例,验证了该方法的可行性。

关键词: 自动钻铆, 定位误差, 定位点布局, 齐次坐标变换, Monte-Carlo法, 多目标优化

Abstract:

In the process of automatic drilling and riveting for large-sized wing panels, the mapping relationship between their practical poses and theoretical poses could not be established accurately due to the large locating errors. Nevertheless, the error compensation process is complicated, which leads to low efficiency in aircraft assembly. Focusing on compensation method through fixture design, locating errors tracing analysis and optimization approach for the layout of locating points are studied aiming to control the locating errors during locating of large-sized wing panels. First, locating errors tracing analysis is carried out according to the process flow of automatic drilling and riveting. The sources of the errors and the propagation mechanism are analyzed. Second, the locating variation propagation process is divided in two sub-process, rigid part and flexible part. For the rigid part, the Monte-Carlo method and the homogeneous transformation method are applied to analyzing the produce and propagation of the errors respectively. As to flexible part, the deformation error of each key feature points on the wing panel is calculated utilizing the finite-element method. Third, combing the rigid part and flexible part, the locating error distributing law is analyzed based on the confidence degree. Fourth, parameterized models are developed using Abaqus scripting language, and the layout of locating points is optimized based on NSGA-II by the means of backstage calling and assignment planning using Isight. Finally, a wing panel of X-type aircraft is used to validate the methodology proposed, which demonstrates the technical feasibility of the methodology.

Key words: automatic drilling and riveting, locating errors, layout of locating points, homogeneous transformation, Monte-Carlo method, multi-objective optimization

中图分类号:

齐振超, 张开富, 李原, 程晖. 大型壁板自动钻铆定位误差分析与优化[J]. 航空学报, 2015, 36(10): 3439-3449.

QI Zhenchao, ZHANG Kaifu, LI Yuan, CHENG Hui. Analysis and optimization for locating errors of large wing panel during automatic drilling and riveting[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(10): 3439-3449.

参考文献

[1] Yang P, Guo Y Z, Li Y L, et al. Dynamic mechanical test of aeronautic rivets[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(11): 3012-3024 (in Chinese). 杨沛, 郭亚洲, 李玉龙, 等. 航空铆钉的动态力学性能测试[J]. 航空学报, 2014, 35(11): 3012-3024.
[2] Han F, Tian W, Liao W H, et al. Normal posture adjustment algorithm for lightweight auto-crawling drilling and riveting system based on parallel mechanism[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(6): 2083-2090 (in Chinese). 韩锋, 田威, 廖文和, 等. 基于并联机构的轻型自主爬行钻铆系统法向调姿算法[J]. 航空学报, 2015, 36(6): 2083-2090.
[3] Qin X S, Wang W D, Lou A L, et al. Three-point bracket regulation algorithm for drilling and riveting of aerofoil[J]. Acta Aeronautica et Astronautica Sinica, 2007, 28(6): 1455-1460 (in Chinese). 秦现生, 汪文旦, 楼阿莉, 等. 大型壁板数控钻铆的三点快速调平算法[J]. 航空学报, 2007, 28(6): 1455-1460.
[4] Yin J Q, Wang Z Q, Kang Y G. Research on riveting process in automatic rivet[J]. Aeronautical Manufacturing Technology, 2014(1): 79-83 (in Chinese). 殷俊清, 王仲奇, 康永刚. 自动钻铆环境下铆接工艺研究[J]. 航空制造技术, 2014(1): 79-83.
[5] Whitney D E. Mechanical assemblies[M]. New York: Oxford University Press, 2004: 35-38.
[6] Xu X S, Yang J X, Cao Y L, et al. Manufacturing error modeling based on homogeneous transformation[J]. Journal of Zhejiang University (Engineering Science), 2008, 42(6): 1021-1026 (in Chinese). 徐旭松, 杨将新, 曹衍龙, 等. 基于齐次坐标变换的制造误差建模研究[J]. 浙江大学学报(工学版), 2008, 42(6): 1021-1026.
[7] Liu S C, Hu S J. Variation simulation for deformable sheet metal assemblies using finite element methods[J]. Journal of Manufacturing Science and Engineering, 1997, 119(3): 368-374.
[8] Dahlström S, Lindkvist L. Variation simulation of sheet metal assemblies using the method of influence coefficients with contact modeling[J]. Journal of Manufacturing Science and Engineering, 2007, 129(3): 615-622.
[9] Jin J H, Shi J J. State space modeling of sheet metal assembly for dimensional control[J]. Transactions of the ASME, 1999, 121(4): 756-762.
[10] Cheng H, Wang R X, Li Y, et al. Modeling and analyzing of variation propagation in aeronautical thin-walled structures automated riveting[J]. Assembly Automation. 2012, 32(1): 25-37.
[11] Hoffman E G. Jig and fixture design[M]. New York: Delmar Publishers, 1991: 46-72.
[12] Rearick M, Hu S J, Wu S M. Optimal fixture design for deformable sheet metal workpieces[J]. Society of Manufacturing Engineers, 1993, 21(2): 407-412.
[13] Cai W. Otimal fixture configuration design for deformable sheet metal part assembly[D]. Michigan: The University of Michigan, 1996.
[14] Camelio J A, Hu S J, Ceglarek D. Impact of fixture design on sheet metal assembly variation[J]. Journal of Manufacturing Systems, 2004, 23(3): 182-193.
[15] Pan Z Y, Hang X, Li Y G. Research and implementation of method of layout design for large tooling in aircraft manufacture[J]. Acta Aeronautica et Astronautica Sinica, 2008, 29(3): 757-762 (in Chinese). 潘志毅, 黄翔, 李迎光. 飞机制造大型工装布局设计方法研究与实现[J]. 航空学报, 2008, 29(3): 757-762.
[16] Jiang C, Han X, Zhong Z H. Locator optimization for resistance-spot-welding fixtures[J]. Journal of Mechanical Engineering, 2009, 45(4): 192-196 (in Chinese). 姜潮, 韩旭, 钟志华. 电阻点焊焊装夹具定位点的优化设计[J]. 机械工程学报, 2009, 45(4): 192-196.
[17] Shi H Y, Liu Y, Yu S J. The locators' layout optimization for flexible sheet metal workpiece using the genetic algorithm[J]. Mechanical Science and Technology, 2012, 31(7): 1145-1149 (in Chinese). 石患云, 刘渝, 余时建. 基于遗传算法的柔性薄板冲压件定位位置优化设计[J]. 机械科学与技术, 2012, 31(7): 1145-1149.
[18] Cheng H, Li Y, Zhang K F, et al. Optimization method of fixture layout for aeronautical thin-walled structures with automated riveting[J]. Assembly Automation, 2012, 32(4): 323-332.
[19] Mu W Q. Research on deformation analysis and compensation of work frame in various position for automatic drill-riveting system[D]. Xi'an: Northwestern Polytechnical University, 2011 (in Chinese). 牟伟强. 自动钻铆系统托架多姿态变形分析及补偿研究[D]. 西安: 西北工业大学, 2011.
[20] Rubinstein R Y, Kroese D P. Simulation and the Monte Carlo method[M]. New York: John Wiley & Sons, 2011: 5-9.
[21] Shen A W, Guo J L, Wang Z J, et al. Validity analysis of reliability evaluation method in aviation equipment field data[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(5): 1311-1318 (in Chinese). 沈安慰, 郭基联, 王卓健, 等. 航空装备现场数据可靠性评估方法有效性分析[J]. 航空学报, 2014, 35(5): 1311-1318.
[22] Davis L. Handbook of genetic algorithms[M]. New York: Van Nostrand Reinhold, 1991: 99-102.
[23] Srinivas N, Deb K. Multiobjective optimization using nondominated sorting in genetic algorithms[J]. Evolutionary Computation, 1994, 2(3): 221-248.
[24] Deb K, Pratap A, Agarwal S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

大型壁板自动钻铆定位误差分析与优化

Analysis and optimization for locating errors of large wing panel during automatic drilling and riveting

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	杨倩, 郑皓冉, 程显达, 董威. 基于引气控制的热气防冰优化设计方法[J]. 航空学报, 2023, 44(S2): 729285-729285.
[2]	董杰忠, 楚武利, 张皓光, 罗波, 晏松. 基于因果网络分析的扩压叶栅波浪形前缘控制机理[J]. 航空学报, 2023, 44(19): 128336-128336.
[3]	毕文豪, 周久力, 段晓波, 张安, 徐双飞. 基于多要素改进NSGA-Ⅱ的小直径制导炸弹空面打击最优火力分配方法[J]. 航空学报, 2023, 44(17): 328116-328116.
[4]	梁超, 杨力, 潘成胜, 戚耀文. 卫星网络动态资源图多QoS约束路由算法[J]. 航空学报, 2023, 44(1): 326422-326422.
[5]	邹子缘, 陈琪锋. 基于决策树搜索的空间飞行器集群对抗目标分配方法[J]. 航空学报, 2022, 43(S1): 726910-726910.
[6]	孙刚, 彭双, 陈浩, 伍江江, 李军. 面向测控数传资源一体化场景的卫星地面站资源多目标优化方法[J]. 航空学报, 2022, 43(9): 326114-326114.
[7]	郑帅, 王子涵, 赵浩然, 杨朋涛, 洪军. 基于差分进化算法的飞机油量传感器布局优化方法[J]. 航空学报, 2022, 43(8): 125809-125809.
[8]	荆涛, 田锡天. 基于蒙特卡洛-自适应差分进化算法的飞机容差分配多目标优化方法[J]. 航空学报, 2022, 43(3): 425278-425278.
[9]	罗庆, 张涛, 单鹏, 张文涛, 刘子豪. 基于改进Q学习的IMA系统重构蓝图生成方法[J]. 航空学报, 2021, 42(8): 525792-525792.
[10]	张军峰, 游录宝, 杨春苇, 胡荣. 基于多目标帝国竞争算法的进场排序与调度[J]. 航空学报, 2021, 42(6): 324439-324439.
[11]	孙刚, 陈浩, 彭双, 杜春, 李军. 一种基于偏好MOEA的卫星地面站资源多目标优化算法[J]. 航空学报, 2021, 42(4): 524475-524475.
[12]	何程, 马东立, 贾玉红, 杨穆清, 陈刚. 联翼布局传感器飞机多目标优化设计[J]. 航空学报, 2021, 42(12): 224761-224761.
[13]	刘继新, 江灏, 董欣放, 兰思洁, 王浩哲. 基于空中交通密度的进场航班动态协同排序方法[J]. 航空学报, 2020, 41(7): 323717-323717.
[14]	孙俊峰, 周铸, 黄勇, 庞宇飞, 卢风顺, 许勇. 通用飞行器气动优化设计数字化集成平台——DIPasda[J]. 航空学报, 2020, 41(5): 623348-623348.
[15]	李润泽, 张宇飞, 陈海昕. 超临界机翼多目标气动优化设计的策略与方法[J]. 航空学报, 2020, 41(5): 623409-623409.