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

• Orginal Article • Previous Articles     Next Articles

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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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

CLC Number: 

  • TP39
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