• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2016, Vol. 52 ›› Issue (21): 35-43.doi: 10.3901/JME.2016.21.035

• 机械学及机器人 • 上一篇    下一篇

基于改进非支配排序遗传算法的正铲挖掘机工作装置优化设计*

徐弓岳1,2, 丁华锋1,2, 孙玉玉1,2   

  1. 1. 先进锻压成型技术与科学教育部重点实验室(燕山大学) 秦皇岛 066004;
    2. 燕山大学河北省并联机器人与机电系统实验室 秦皇岛 066004
  • 出版日期:2016-11-05 发布日期:2016-11-05
  • 作者简介:徐弓岳,男,1990年出生,博士研究生。主要研究方向为机构综合与机械优化设计。

    E-mail:xgy_ztt@163.com

    丁华锋(通信作者),男,1977年出生,博士,教授,博士研究生导师。主要研究方向为机构综合及机械装备的创新设计。

    E-mail:dhf@ysu.edu.cn

  • 基金资助:
    * 国家优秀青年科学基金(51422509)和国家自然科学基金(51275437)资助项目; 20151110收到初稿,20160825收到修改稿;

Optimization of Face-shovel Excavator’s Attachment Based on Improved NSGA-II

XU Gongyue1,2, DING Huafeng1,2, SUN Yuyu1,2   

  1. 1. Key Laboratory of Advanced Forging & Stamping Technology and Science (Yanshan University),Ministry of Education of China, Qinhuangdao 066004;
    2. Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao 066004
  • Online:2016-11-05 Published:2016-11-05

摘要:

采用多目标进化算法对正铲挖掘机工作装置进行优化设计,目标是水平直线挖掘铲斗切削后角变化量、主要挖掘区域内纵向斗杆挖掘最大挖掘力和纵向铲斗挖掘最大挖掘力3个性能指标。针对NSGA-II处理具有复杂Pareto最优前端优化问题能力不足的问题,提出动态拥挤排序策略,提高算法求解的多样性,引入差分算子和柯西变异算子,提高算法的全局寻优能力。使用ZDT系列测试函数对改进算法进行测试研究,结果表明改进算法的收敛性指标和多样性指标均有很大提高,能够很好地处理具有复杂Pareto最优前端的优化问题。基于改进的优化算法对正铲挖掘机工作装置进行优化设计,并利用理想解法得到了最满意优化方案,优化结果表明了改进算法应用于实际工程问题的有效性和可行性。

关键词: NSGA-II, 多目标优化, 工作装置, 理想解法, 正铲挖掘机

Abstract: A multi-objective evolutionary algorithm is applied to optimize the face-shovel excavator attachment, which sets the variable quantity of bucket’s cutting angle in excavating along horizontal line, the stick digging force and the bucket digging force in vertical direction in main digging range as optimization goals. Aiming at improving the performance of NSGA-II in the optimization problems of complicated Pareto front, a dynamic sorting algorithm is designed to improve the diversity. Differential evolution operator and Cauchy mutation operator are proposed for improving the convergency and the ability of global optimization. By using a class of continuous multi-objective optimization test instances to test the improved NSGA-II, the experimental results indicate that the proposed algorithm could significantly outperform NSGA-II on these test instances. The proposed algorithm is applied to a practical example of face-shovel excavator, and can make use of TOPSIS to select the most satisfied schedule from the Pareto set. The comparison with other schemes testifies the feasibility and effectiveness of the improved NSGA-II.

Key words: multi-objective optimization, NSGA-II, technique for order preference by similarity to ideal solution, working device, face-shovel excavator