首页|基于响应面法的机载光电集成箱优化设计

基于响应面法的机载光电集成箱优化设计

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机载光电集成箱在战斗机飞行过程中面临振动、冲击等恶劣工作环境.本文旨在提高光电集成箱抗振动干扰能力和结构可靠性,以减少最大变形量和提升结构一阶模态频率为目标,对光电集成箱进行多目标优化设计.根据加速度过载极端条件对原始光电集成箱三维模型进行特定载荷下的静力分析和普通约束条件下的模态分析;采用最佳空间填充设计法(OSFD)法进行实验设计,提取结构设计参数并建立样本空间,响应面模型运用Kriging法进行构建;以最小化结构变形量、提升结构第一阶模态频率作为优化目标,以结构等效应力和质量为约束条件,运用MOGA遗传算法对构建响应面模型进行了优化求解,得到响应面模型最优解,最后对模型进行参数化重构和验证.优化结果显示:经过优化后的光电集成箱,最大变形量减少了 44.02%,基频提高了 33.6%,质量减少了 8%,有效地提升了光电集成箱的动力学性能和可靠性.
Optimization Design of Airborne Photoelectric Integrated Box Based on Response Surface Methodology
The airborne photoelectric integrated box is faced with the harsh working environment such as vibration and shock during the flight of fighter aircraft.In order to reduce the maximum deformation and increase the first mode frequency of the structure,the multi-objective optimization design of the photoelectric integrated box is carried out in order to improve the vibration resistance and structural reliability.According to the extreme condition of acceleration overload,the static analysis under specific load and the modal analysis under ordinary constraint are carried out on the 3D model of the original photoelectric integrated box.The Optimal Space-Fulling Design(OSFD)method was used for experimental design.Structural design parameters were extracted and sample space was established.The response surface model was constructed by Kriging method.To minimize the structural deformation and increase the first-order modal frequency of the structure,taking the equivalent stress and mass of the structure as constraints,MOGA genetic algorithm was used to optimize and solve the response surface model.The optimal solution of the response surface model was obtained.Finally,the model was reconstructed and verified parametrically.The optimization results show that the maximum deformation is reduced by 44.02%,the fundamental frequency is increased by 33.6%,and the mass is reduced by 8%,which effectively improves the dynamic performance and reliability of the photoelectric integrated box.

optimal space-fulling design(OSFD)Kriging methodmulti-objective genetic algorithmresponse surface optimization

陶冶、农王亮、苏润石、李克凯、马晓国

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四川大学机械工程学院,四川成都 610065

最佳空间填充设计法 Kriging法 多目标遗传算法 响应面优化

四川省科技计划重点研发项目四川大学遂宁校市战略合作"揭榜挂帅"科技项目

2021YFG01932021CDSN-14

2024

机械
四川省机械研究设计院 四川省机械工程学会 四川省机械科技情报标准研究所

机械

影响因子:0.392
ISSN:1006-0316
年,卷(期):2024.51(1)
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