基于智能水滴算法的装夹规划方法

中国机械工程

基于智能水滴算法的装夹规划方法

高博;胡晓宇;彭珍瑞;刘君泉

兰州交通大学机电工程学院，兰州，730070

出版日期:2019-11-10 发布日期:2019-11-08
基金资助:
国家自然科学基金资助项目（51768035,61463028）

Setup Planning Method Based on Intelligent Water Drops Algorithm

GAO Bo;HU Xiaoyu;PENG Zhenrui;LIU Junquan

School of Mechanical Engineering,Lanzhou Jiaotong University,Lanzhou,730070

Online:2019-11-10 Published:2019-11-08

摘要/Abstract

摘要： 针对计算机辅助工艺设计中的装夹规划问题，提出一种基于智能水滴算法的装夹规划方法。通过对加工特征进行分析来定义零件的操作单元及其约束关系，构建装夹规划的模型。将零件的各个操作单元与智能水滴算法中流动路径的各个节点相关联，利用水滴所携带的泥土量来表征操作单元之间的相似度，以此来构建智能水滴算法的适应度函数。在经过操作单元顺序约束矩阵所筛选出的可行解空间内进行迭代求解，通过水滴多次冲刷路径中的泥土量来筛选最优解,解码后获得了最优的装夹规划方案。以典型零件的装夹规划为例，验证了该方法的有效性和可行性。

关键词: 装夹规划, 智能水滴算法, 适应度函数, 计算机辅助工艺规划

Abstract: To solve the setup planning problems in CAPP, a novel setup planning method was proposed based on intelligent water drops(IWD) algorithm. By analyzing the machining features, the machining unit and its constraint relationships were defined, and the setup planning model was constructed. The machining units of the parts were associated with the nodes of the flow path in IWD algorithm, and then the similarity between machining units was characterized by the amount of soil carried by the water-drop, thus the fitness function of IWD algorithm was constructed. Iterative computation was carried out in the feasible solution space selected by the sequential constraint matrix of the machining unit. The optimal solution was obtained by the amount of soil in the path of water droplet scour for several times, and the optimal setup planning was obtained after decoding. Setup planning process of the typical parts was illustrated to prove the effectiveness and feasibility of the proposed method.

Key words: setup planning, intelligent water drops(IWD) algorithm, fitness function, computer aided process planning（CAPP）

中图分类号:

TP391

高博;胡晓宇;彭珍瑞;刘君泉. 基于智能水滴算法的装夹规划方法[J]. 中国机械工程.

GAO Bo;HU Xiaoyu;PENG Zhenrui;LIU Junquan. Setup Planning Method Based on Intelligent Water Drops Algorithm[J]. China Mechanical Engineering.

参考文献

[1]SU Y, CHU X, CHEN D, et al. A Genetic Algorithm for Operation Sequencing in CAPP Using Edge Selection Based Encoding Strategy[J]. Journal of Intelligent Manufacturing, 2017(9/10):1-20.
[2]高博，阎艳，张发平，等. 基于文化基因算法的装夹规划方法[J]. 机械工程学报，2015，51(3)：162-169.
GAO Bo, YAN Yan, ZHANG Faping, et al. Setup Planning Method Based on Memetic Algorithm[J]. Journal of Mechanical Engineering, 2015, 51(3):162-169.
[3]YAO S, HAN X, YANG Y, et al. Computer Aided Manufacturing Planning for Mass Customization: Part 2, Automated Setup Planning[J]. International Journal of Advanced Manufacturing Technology, 2007, 32(1/2):205-217.
[4]SUN X W, CHU X N, SU Y L, et al. A New Directed Graph Approach for Automated Setup Planning in CAPP[J]. International Journal of Production Research, 2010, 48(22):6583-6612.
[5]高博，阎艳，张发平，等. 基于公差推理的零件聚类装夹规划方法研究[J]. 北京理工大学学报，2015，35(3)：236-241.
GAO Bo, YAN Yan, ZHANG Faping, et al. Research on Clustering Setup Planning of Part Based on Tolerance Reasoning[J]. Transactions of Beijing Institute of Technology, 2015, 35(3):236-241.
[6]HUANG W, HU Y, CAI L. An Effective Hybrid Graph and Genetic Algorithm Approach to Process Planning Optimization for Prismatic Parts[J]. International Journal of Advanced Manufacturing Technology, 2012, 62(9/12):1219-1232.
[7]KAFASHI S. Integrated Setup Planning and Operation Sequencing(ISOS) Using Genetic Algorithm[J]. International Journal of Advanced Manufacturing Technology, 2011, 56(5/8):589-600.
[8]GUO Y W, LI W D, MILEHAM A R, et al. Applications of Particle Swarm Optimisation in Integrated Process Planning and Scheduling[J]. Robotics and Computer-integrated Manufacturing, 2009, 25(2):280-288.
[9]常智勇，杨建新，赵杰，等. 基于自适应蚁群算法的工艺路线优化[J]. 机械工程学报，2012，48(9)：163-169.
CHANG Zhiyong, YANG Jianxin, ZHAO Jie, et al. Optimization of Process Based on Adaptive Ant Colony Algorithm[J]. Journal of Mechanical Engineering, 2012, 48(9):163-169.
[10]黄风立，左春柽，顾金梅，等. 基于加工操作单元的多态蚁群装夹规划方法[J]. 机械工程学报，2017，53(7)：164-172.
HUANG Fengli, ZUO Chuncheng, GU Jinmei, et al. Polymorphic Ant Colony Clamping Planning Method Based on the Machining Operation Unit[J]. Journal of Mechanical Engineering, 2017, 53(7):164-172.
[11]LI W D, ONG S K, NEE A Y C. Hybrid Genetic Algorithm and Simulated Annealing Approach for the Optimization of Process Plans for Prismatic Parts[J]. International Journal of Production Research, 2002, 40(8):1899-1922.
[12]宋晓琳，潘鲁彬，曹昊天. 基于改进智能水滴算法的汽车避障局部路径规划[J]. 汽车工程，2016，38(2)：185-191.
SONG Xiaolin, PAN Lubin, CAO Haotian. Local Path Planning for Vehicle Obstacle Avoidance Based on Improved Intelligent Water Drops Algorithm[J]. Automotive Engineering, 2016, 38(2):185-191.
[13]SHAH-HOSSEINI H. Intelligent Water Drops Algorithm: A New Optimization Method for Solving the Multiple Knapsack Problem[J]. International Journal of Intelligent Computing and Cybernetics, 2008, 1(2):193-212.