吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (6): 1903-1908.doi: 10.13229/j.cnki.jdxbgxb201706031

• 论文 • 上一篇    下一篇

机械零部件动态可靠性稳健优化设计的群智能算法

于繁华1, 刘仁云2, 张义民3, 张晓丽1, 3, 孙秋成1   

  1. 1.长春师范大学 计算机科学与技术学院,长春 130032;
    2.长春师范大学 数学学院,长春 130032;
    3.东北大学 机械工程与自动化学院,沈阳 110004
  • 收稿日期:2016-09-12 出版日期:2017-11-20 发布日期:2017-11-20
  • 通讯作者: 刘仁云(1968-),女,教授,博士.研究方向:计算智能,结构可靠性设计与优化.E-mail:liurenyun2005@163.com
  • 作者简介:于繁华(1970-),男,教授,博士.研究方向:计算智能及应用.E-mail:yufanhua@163.com
  • 基金资助:
    吉林省产业创新专项资金项目(2017C031-2); 吉林省教育厅项目(吉教科合字[2014]第17号、吉教科合[2013]第243号)

Swarm intelligence algorithm of dynamic reliability-based robust optimization design of mechanic components

YU Fan-hua1, LIU Ren-yun2, ZHANG Yi-min3, ZHANG Xiao-li1, 3, SUN Qiu-cheng1   

  1. 1.College of Computer Science & Technology, Changchun Normal University, Changchun 130032, China;
    2.College of Mathematics, Changchun Normal University, Changchun 130032, China;
    3.College of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004, China
  • Received:2016-09-12 Online:2017-11-20 Published:2017-11-20

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摘要： 在运用随机过程和顺序统计原理建立载荷和强度随时间变化的动态可靠性模型基础上,利用稳健设计理论,建立了机械零部件动态可靠性稳健优化设计的多目标优化模型。针对该多目标模型所具有的动态高维的特点,提出了基于灰色关联分析的多粒子群协同动态多目标优化算法。以钢板弹簧结构为例,给出了动态环境下随时间变化的最优解集,为机械零部件的动态可靠性稳健优化设计提供了理论依据。

关键词: 计算机应用, 极端学习机, 动态粒子群算法, 可靠性优化设计, 多目标优化

Abstract: A dynamic reliability-based model, whose load and strength vary with time, is established by using random process and order statistics theory. Then, applying robust optimization design theory, a multi-objective optimization model is proposed for the dynamic reliability-based robust design of mechanic components. Considering the dynamic high-dimensional characteristics of the proposed model, a multiple particle swarm co-evolutionary algorithm based on grey correlation analysis theory is developed for the multi-objective optimization. The leaf-spring is taken as an example for solving the optimal solution set in dynamic environment. Results demonstrate that the proposed method can provide theoretical foundation for dynamic reliability-based robust design of mechanic components.

Key words: computer application, extreme learning machine, dynamic particle swarm algorithm, reliability optimization design, multi-objective optimization

中图分类号: 

  • TP39
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