多层吸波材料结构优化仿真研究
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摘要
研究多层吸波材料的结构优化问题。通过优化多层吸波材料的结构,可以增强材料对雷达波的吸收,提升材料的隐身能力。传统算法在解决多层吸波材料结构优化问题时,收敛速度较慢,寻优精度较低。为解决上述问题,提出一种改进遗传算法,以各层材料的种类和厚度为优化变量,以不同频段的吸收频带宽度为优化目标,采用动态编码及跟踪解码、精英选择策略和动态遗传算子等技术,提高收敛速度,避免了收敛于局部最优值。利用改进后的遗传算法进行仿真,并与标准遗传算法进行对比。仿真结果表明,改进后的遗传算法收敛速度更快,寻优能力更强,能有效解决多层吸波材料的结构优化问题。
The structure optimization of multi-layer microwave absorbers is researhed. Considering the low precision and the slow convergence speed of traditional algorithms in the structure optimization of multi-layer microwave absorbers, the Improved Genetic Algorithm is put forward.. Taking the type and thickness of each layer material as the optimization variables and the absorbing bandwidth as the optimization objective, the dynamic encoding and dynamically tracing decoding, elitism strategy and dynamic genetic operator were used to increase the convergence speed and avoid converging on local optimum. Compared the Improved Genetic Algorithm with the Genetic Algorithm, the simulation result show that the Improved Genetic Algorithm has faster convergence speed,better global search ability and effectiveness.
The structure optimization of multi-layer microwave absorbers is researhed. Considering the low precision and the slow convergence speed of traditional algorithms in the structure optimization of multi-layer microwave absorbers, the Improved Genetic Algorithm is put forward.. Taking the type and thickness of each layer material as the optimization variables and the absorbing bandwidth as the optimization objective, the dynamic encoding and dynamically tracing decoding, elitism strategy and dynamic genetic operator were used to increase the convergence speed and avoid converging on local optimum. Compared the Improved Genetic Algorithm with the Genetic Algorithm, the simulation result show that the Improved Genetic Algorithm has faster convergence speed,better global search ability and effectiveness.
引文
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[2]李超,等.复合型雷达吸波材料结构优化设计的数值计算[J].宇航材料工艺,2008,38(5):12-16.
[3]张跃,张明雪.多目标规划方法在隐身涂层设计中的应用[J].宇航材料工艺,2001,31(6):63-66.
[4]袁杰,等.多层吸波材料的计算机辅助优化设计[J].哈尔滨工程大学学报(英文版),2000,21(2):51-54.
[5]肖怀宝,逯贵祯,关亚林.模拟退火算法研究混合结构吸波材料特性[J].中国传媒大学学报(自然科学版),2009,16(3):45-47.
[6]晁坤,刘运林,杨儒贵.蚁群算法结合微遗传算法优化设计多层雷达吸波涂层[J].功能材料,2008,39(6):1052-1055.
[7]EMichielssen,et al.Design of lightweight,broad-band microwav absorbers using genetic algorithms[J].IEEE Transactions on Microwave Theory&Techniques,1993,41(6):1024-1031.
[8]甘治平,等.用遗传算法设计宽带薄层微波吸收材料[J].电子学报,2003,31(6):918-920.
[9]李元奇.弓形法对吸波材料反射率的变温测试研究[D].电子科技大学,2011.
[10]TGiannakopoulou,et al.Microwave behavior of ferrites prepare via sol-gel method[J].Journal of Magnetism&Magnetic Ma terials,2002,246(3):360-365.
[11]张鸿雁,普乐.最优保存遗传算法在最优资产组合计算中的应用[J].数学理论与应用,2002,(1):46-50.