【摘要】 超磁致伸缩材料(Giant magnetostrictive material,GMM)因为具有大应变和热鲁棒性等优良特性而应用广泛。超磁致伸缩材料器件设计中涉及电-磁-机等多个场能量转化,现有的设计主要利用经验公式。针对一种利用GMM智能加工活塞异形孔系统,建立一种综合考虑驱动线圈时间常数、驱动线圈电感、系统一阶固有频率、电磁转化系数及镗杆构件径向变形量为目标的多目标多约束优化设计模型,提出一种耦合有限元计算和非支配排序遗传算法(NSGA-II)计算模型,根据此模型优化结果设计GMM智能加工活塞异形孔系统。所建立的模型及提出的实现方法,对智能化设计GMM器件具有一定的借鉴。更多还原

【Abstract】 Giant magnetostrictive material(GMM)with large strain and thermal robustness and other characteristics is widely used. The design of the giant magnetostrictive device involved the transformation of multi-field including electric field,magnetic field, mechanical field. The existing design methods are using an empirical formula. In this paper, a multi-objective with multi-constrained design model was proposed for GMM intelligent machining piston shaped orifice system. A multi-objective with multi-constrained optimization model considered the time constant of driving coil, the inductance of drive coil,the first order natural frequency of system, the electromagnetic conversion coefficient and boring bar radial deformation. A coupling finite element calculation and genetic algorithm(NSGA-Ⅱ)for resolving the model was proposed. According to the optimization results, a GMM intelligent processing piston shaped hole system was designed and produced.The established model and the proposed implementation method provide reference for intelligent GMM device design.更多还原