基于新型粒子群算法的结构动力学热振模型修正

doi:10.7527/S1000-6893.2022.26559

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基于新型粒子群算法的结构动力学热振模型修正

王震宇¹,王计真²,杨婧艺¹,何鹏远¹,潘成浩¹,周凌波³,何成⁴,何欢¹

1. 南京航空航天大学
2. 中国飞机强度研究所
3. 中国船舶科学研究中心
4. 南京航空航天大学振动工程研究所;机械结构力学及控制国家重点实验室

收稿日期:2021-10-25 修回日期:2022-03-16 出版日期:2022-03-22 发布日期:2022-03-22
通讯作者: 何欢
基金资助:
国家自然科学基金

Dynamics Model Updating of Structures under High Temperature based on A Novel Particle Swarm Optimization Algorithm

Received:2021-10-25 Revised:2022-03-16 Online:2022-03-22 Published:2022-03-22
Contact: Huan HE
Supported by:
National Natural Science Foundation of China

摘要/Abstract

摘要： 本文提出一种基于新型粒子群算法的结构动力学热振模型修正方法，并成功应用于高温环境下典型复杂多组件结构的模型修正问题中。为了克服粒子群算法解决模型修正等非线性优化问题时早熟收敛的缺点，本文联合莱维飞行策略和正交学习方法提出莱维正交学习粒子群优化算法。在研究中，该方法和其他优化算法被用于修正轴系轴承-轴承座的等效刚度和阻尼参数，通过比较证明该新型算法具有更高的精度；最后本文针对典型复杂多组件结构在高温环境下的振动实验进行模型修正，修正后不同温度环境下各阶模态频率误差均下降到7%以内，有限元模型精度得到极大地提高，表明该方法可以有效应用于工程实际。

关键词: 粒子群算法, 莱维飞行, 正交学习, 高温环境, 有限元, 模型修正

Abstract: A novel particle swarm optimization(PSO) based dynamics model updating method of structurals under high temperature environment was proposed and applied to update the finite element(FE) model of a typical complex multi-component structure. Firstly, the LFOLPSO algorithm was designed by combining the Lévy flight strategy and orthogonal learning method to overcome shortcomings of premature convergence when the PSO solves nonlinear optimization problems such as parameter identification and model updating. Then the proposed method was used to update the equivalent stiffness and damping parameters of shafting bearings. It was proved that the new algorithm has higher accuracy. Finally, we updated the FE model of a typical complex multi-component structure in high temperature environment based on the vibration experiment by the LFOLPSO method. After updating, the errors of mian modal frequencies under different temperature environments were reduced to less than 7%. The accuracy of the FE model had been greatly improved to verify the effectiveness of the proposed method and its applicability for actual engineering problems.

Key words: Particle swarm optimization, Lévy flight, Orthogonal learning, High temperature, FEM, Model updating

中图分类号:

V219
214.5

王震宇王计真杨婧艺何鹏远潘成浩周凌波何成何欢. 基于新型粒子群算法的结构动力学热振模型修正[J]. 航空学报, doi: 10.7527/S1000-6893.2022.26559.

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E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于新型粒子群算法的结构动力学热振模型修正

Dynamics Model Updating of Structures under High Temperature based on A Novel Particle Swarm Optimization Algorithm

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