计算机应用 ›› 2010, Vol. 30 ›› Issue (3): 786-788.

• 人工智能 • 上一篇    下一篇

带飞行因子的粒子群算法的铝蜂窝夹层板模型修正

孔宪仁1,秦玉灵2,罗文波3   

  1. 1. 哈尔滨工业大学 卫星技术研究所
    2. 哈尔滨工业大学
    3. 中国空间技术研究院
  • 收稿日期:2009-09-11 修回日期:2009-10-23 发布日期:2010-03-14 出版日期:2010-03-01
  • 通讯作者: 秦玉灵
  • 基金资助:
    长江学者和创新团队发展计划资助项目

Model updating of aluminum honeycomb sandwich plate based on particle swarm optimization algorithm with flying factor

  • Received:2009-09-11 Revised:2009-10-23 Online:2010-03-14 Published:2010-03-01

摘要: 蜂窝板结构具有较高的比强度、比刚度和良好的隔热隔振、耐冲击等优点,在航空航天领域得到了广泛应用。根据等效板理论将蜂窝夹层板等效为壳单元,以试验测得的前五阶模态频率为基础,用带飞行因子的粒子群算法对其材料等效密度和刚度参数进行模型修正,修正后模型计算频率与试验值误差较原误差有了明显减小,与标准粒子群算法相比,带飞行因子粒子群算法修正后的模型能更好地逼近原结构,模型质量有了改善。证实了带飞行因子粒子群算法在模型修正过程中的可行性和有效性。

关键词: 蜂窝板, 等效板理论, 粒子群算法, 飞行因子, 材料参数, 模型修正

Abstract: Honeycomb sandwich plate has high specific strength, high specific stiffness and good heat insulation, vibration insulation as well as impact resistance, which makes it widely used in the aerospace engineering. The honeycomb sandwich plate was made to be equivalent to shell element according to the equivalent plate theory, and based on the first five natural frequencies of the modal test, the Particle Swarm Optimization (PSO) algorithm with flying factor was used to update the material parameters such as the equivalent stiffness and equivalent density and the results show that the updated natural frequencies approach the test data better than the non-updated ones. Compared with the standard PSO algorithm, the Finite Element Model (FEM) updated by PSO with flying factor can approach the real structure better, which proves the validity and efficiency of this algorithm.

Key words: honeycomb sandwich plate, equivalent plate theory, Particle Swarm Optimization (PSO) algorithm, flying factor, material parameter, model updating