易少强, 何世平, 王杰. 粒子群算法在约束型垫高阻尼结构动力学优化中的应用[J]. 中国舰船研究, 2018, 13(1): 31-37. DOI: 10.3969/j.issn.1673-3185.2018.01.005
引用本文: 易少强, 何世平, 王杰. 粒子群算法在约束型垫高阻尼结构动力学优化中的应用[J]. 中国舰船研究, 2018, 13(1): 31-37. DOI: 10.3969/j.issn.1673-3185.2018.01.005
YI Shaoqiang, HE Shiping, WANG Jie. Application of particle swarm optimization in dynamic optimization of constrained stand-off layer damping structure[J]. Chinese Journal of Ship Research, 2018, 13(1): 31-37. DOI: 10.3969/j.issn.1673-3185.2018.01.005
Citation: YI Shaoqiang, HE Shiping, WANG Jie. Application of particle swarm optimization in dynamic optimization of constrained stand-off layer damping structure[J]. Chinese Journal of Ship Research, 2018, 13(1): 31-37. DOI: 10.3969/j.issn.1673-3185.2018.01.005

粒子群算法在约束型垫高阻尼结构动力学优化中的应用

Application of particle swarm optimization in dynamic optimization of constrained stand-off layer damping structure

  • 摘要:
      目的  为了进一步提高传统约束型阻尼结构的振动特性,对改进后的约束型垫高阻尼结构进行优化设计。
      方法  首先,根据薄板弯曲理论和Hamilton变分原理探讨约束型垫高阻尼结构的动力学特性;其次,阐述粒子群算法迭代寻优的基本原理,提出优化含连续变量和离散变量的粒子群算法;最后,结合约束型垫高阻尼结构的动力学特性,运用改进的粒子群算法实现结构的优化配置。
      结果  当算法搜索寻优到第12代时结果趋于稳定,表明算法已收敛。
      结论  研究表明,粒子群算法能较好地求解约束型垫高阻尼结构动力学优化问题,且获得的最优化解可被应用于工程实际。

     

    Abstract:
      Objectives  In order to further improve the vibration characteristics of traditional constrained damping structures, the optimized design of an improved constrained stand-off layer damping structure with engineering application value is carried out.
      Methods  First, based on the thin plate bending theory and Hamilton variation principle, the dynamic characteristics of constrained stand-off layer damping structures are investigated; second, the basic principle of the iterative optimization of particle swarm optimization is expounded upon, and a particle swarm optimization algorithm with continuous variables and discrete variables proposed; finally, combined with the dynamic characteristics of constrained stand-off layer damping structures, the improved particle swarm optimization is used to realize the optimal allocation of the structure.
      Results  When the search algorithm is optimized to the 12th generation, the algorithm tends to be stable, indicating that it is convergent.
      Conclusions  The optimization results show that the particle swarm optimization can better solve the dynamic optimization problem of constrained stand-off layer damping structures, and obtain an optimal solution that can be applied in practical engineering.

     

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