磁控形状记忆合金力—磁—热耦合行为及控制策略的研究

发布时间：2018-06-20 13:44

本文选题：MSMA + 多场耦合驱动性能　；参考：《武汉科技大学》2015年硕士论文

【摘要】：磁控形状记忆合金（Magnetic Shape Memory Alloy，简称MSMA）是近年来出现的一种新型功能材料，该材料在磁场作用下可获得较大的磁感生应变，具有输出应变大、响应速度快、能量密度高等优良特性，，有望作为一种新型驱动材料应用于工业执行器件。本文以单晶Ni2MnGa磁控形状记忆合金为研究对象，对其力磁热多场耦合作用下的驱动力学特性进行实验研究与预测、并基于多场耦合实验数据对MSMA驱动器磁控回路优化设计及磁滞补偿控制策略进行了初步探讨。主要研究内容如下：（1）对MSMA力磁热多场耦合驱动力学性能进行实验测试，总结预加应力、控制磁场及工作温度与MSMA形变率之间的规律关系，并通过MSMA磁致形变机制对其进行了初步解释。基于MSMA力磁热多场耦合驱动实验数据，利用BP神经网络建立了MSMA驱动行为预测模型，并通过遗传算法对其进行适当优化，实现了MSMA输入变量（预加应力、控制磁场、工作温度）与输出变量（MSMA形变率）之间较好的对应关系。（2）针对目前MSMA驱动器大多采用励磁线圈产生控制磁场，驱动工作过程中励磁线圈散发热量容易导致MSMA驱动元件工作温度升高，影响驱动器控制精度的问题。本文提出一种基于永磁体偏置磁场及温度冷却装置的MSMA驱动器磁控回路优化设计方案，并利用有限元分析软件对磁控回路进行了电磁场、温度场的仿真分析，仿真结果验证了磁控回路设计的合理性。（3）通过对MSMA驱动器进行建模，得出MSMA驱动器输入电压与输出位移之间的关系式；基于MSMA驱动器固有的磁滞非线性，建立MSMA驱动器磁滞模型，采用PID与磁滞正模型的闭环控制以及PID与磁滞正逆模型混合的复合控制两种控制策略对MSMA驱动器进行磁滞补偿，结果表明：两种控制策略均可大大减弱MSMA驱动器固有的磁滞非线性，但PID与磁滞正模型的闭环控制效果最佳。
[Abstract]:Magnetic shape memory alloy (MSMA) is a new type of functional material which has been developed in recent years. It can obtain large magnetically induced strain under the action of magnetic field. It has the advantages of large output strain, fast response speed and high energy density. It is expected to be used as a new type of driving material in industrial executive devices. In this paper, the driving force characteristics of single crystal Ni _ 2MnGa magnetically controlled shape memory alloy under the multi-field coupling are studied and predicted experimentally. Based on the experimental data of multi-field coupling, the optimization design and hysteresis compensation control strategy of MSMA driver magnetic control loop are discussed. The main research contents are as follows: (1) the mechanical properties of MSMA with magnetocalorimetric coupling drive are experimentally tested, and the relationship between pre-stress, control of magnetic field and working temperature and the deformation rate of MSMA is summarized. The MSMA magnetodeformed mechanism was preliminarily explained. Based on the experimental data of MSMA magnetocalorimetric multi-field coupling drive, the prediction model of MSMA driving behavior is established by using BP neural network, and the MSMA input variable (pre-stress, magnetic field control) is realized by genetic algorithm (GA). Working temperature) and output variable MSMA deformation rate). The heat emission from the excitation coil in the driving process can easily lead to the increase of the operating temperature of the MSMA driving element, which affects the control accuracy of the driver. In this paper, an optimal design scheme of magnetic control loop of MSMA driver based on permanent magnet bias magnetic field and temperature cooling device is proposed, and the simulation analysis of electromagnetic field and temperature field of magnetic control loop is carried out by using finite element analysis software. The simulation results verify the rationality of the design of the magnetic control loop. By modeling the MSMA driver, the relationship between the input voltage and the output displacement of the MSMA driver is obtained, which is based on the inherent hysteresis nonlinearity of the MSMA driver. The hysteresis model of MSMA driver is established. The closed loop control of pid and hysteresis positive model and the hybrid control of pid and hysteresis inverse model are used to compensate the hysteresis of MSMA driver. The results show that both control strategies can greatly reduce the inherent hysteresis nonlinearity of MSMA driver, but the closed-loop control effect of pid and hysteresis positive model is the best.
【学位授予单位】：武汉科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TB34

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