吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (4): 1269-1275.doi: 10.13229/j.cnki.jdxbgxb201604037

• Orginal Article • Previous Articles     Next Articles

Intelligent algorithm for optimized dynamic reliability design of mechanic structure

YU Fan-hua1, LIU Ren-yun2, ZHANG Yi-min3, SUN Qiu-cheng2, ZHANG Xiao-li2, 3   

  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:2015-04-13 Online:2016-07-20 Published:2016-07-20

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Abstract: A Monte Carlo time-varying extreme learning machine is presented for dynamic reliability design of mechanical components under multiple failure modes. The explicit function expression of the reliable degree of these variables, such as the loads, strength, elastic modulus and design parameters, can be obtained by this model. Then, on this basis, a dynamic reliability design model for the mechanical components is established, and the dynamic particle swarm algorithm is applied for the solution of this model. Experiment results show that this method can provide all design parameters meeting the requirement of the reliable degree in the whole service life. This method can be used as an effective approach for optimized dynamic reliability design of mechanical 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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