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基于蚁群遗传算法的超磁致伸缩材料迟滞模型优化研究

GMM hysteresis model based on ant colony optimization genetic algorithm
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摘要 超磁致伸缩材料(GMM)是一种新型的智能材料,GMM制作的超磁致伸缩执行器(GMA)在航空、微定位等领域得到广泛应用。本文对GMA设计中的Terfenol-D特性进行优化,基于蚁群遗传算法对超磁致伸缩材料迟滞模型进行优化,建立了基于Terfenol-D棒上超磁致伸缩执行器磁回路。通过优化,磁通分布及线圈功率转化系数呈现明显的提高。 Giant magnetostrictive material(GMM) is a new kind of intelligent material, GMM made of giant magnetostrictive actuator(GMA) is widely applied in aviation, micro positioning, and other fields.In this paper, the design of GMA Terfenol- D feature optimization, genetic algorithm based on ant colony hysteresis model of giant magnetostrictive material is optimized, based on Terfenol- D stick on giant magnetostrictive actuator magnetic circuit.Through optimization, the magnetic flux distribution and coil power conversion coefficient is obviously improved.
出处 《世界有色金属》 2016年第10期75-78,共4页 World Nonferrous Metals
基金 国家自然科学基金资助项目(51075001)
关键词 超磁致伸缩材料迟滞模型 Terfenol-D棒 蚁群遗传算法 多目标优化 giant magnetostrictive material field model Terfenol-D rod ant colony algorithm with genetic algorithm multiobjective optimization
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