面向力学性能的并联隔振平台结构参数优化设计
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  • 英文篇名:Mechanical-perfomance-oriented optimization design of vibration isolation platform based on parallel mechanism
  • 作者:程明 ; 陈照波 ; 方宇娟 ; 刘潇
  • 英文作者:CHENG Ming;CHEN Zhao-bo;FANG Yu-juan;LIU Xiao-xiang;School of Mechatronics Engineering,Harbin Institute of Technology;The School of Computer and Information,Anhui Polytechnic University;Beijing Institute of Control Engineering;
  • 关键词:隔振平台 ; 并联机构 ; 结构参数优化 ; 静变形量 ; 遗传算法
  • 英文关键词:vibration isolation platform;;parallel mechanisms;;structural parameters optimization;;static deformation;;genetic algorithm
  • 中文刊名:ZDGC
  • 英文刊名:Journal of Vibration Engineering
  • 机构:哈尔滨工业大学机电工程学院;安徽工程大学计算机与信息学院;北京控制工程研究所;
  • 出版日期:2019-02-15
  • 出版单位:振动工程学报
  • 年:2019
  • 期:v.32
  • 基金:国家自然科学基金资助项目(11372083,61304037)
  • 语种:中文;
  • 页:ZDGC201901001
  • 页数:9
  • CN:01
  • ISSN:32-1349/TB
  • 分类号:5-13
摘要
固有频率和静变形量是度量并联隔振平台的力学性能的两个重要指标,其可以通过优化平台的结构参数得到综合提升,实现在保证静态刚度要求的前提下拓宽隔振平台的有效隔振带宽。通过对并联平台结构参数优化问题的描述及其影响因素的分析,建立以横向一阶固有频率、纵向一阶固有频率以及静变形量为目标,以上下平台半径、平台高度、负载质心高度、支腿与上下平台铰接点的中心夹角、弹簧刚度以及负载质量为变量的结构参数优化模型。选取两两之间关联度较大的4组变量,交互分析其对优化目标的影响。进一步,采用非支配排序遗传算法NSGA-Ⅱ进行模型优化求解,寻找最优结构参数。最后,通过实例对比显示优化后的隔振平台的力学性能得到明显改善。
        The natural frequency and the static deformation are two important factors to indicate the mechanical performance of the vibration isolation platform based on parallel mechanism.These two factors can be comprehensively improved through optimizing the structural parameters of the platform,thus broading the effective vibration isolation bandwidth with meanwhile meeting the static stiffness requirements.Based on the description of the optimization problem and analysis of its impact factors,a multi-objective optimization model,which takes the static deformation and the first natural frequency in the transverse and longitudinal direction respectively as the optimization objectives,the radius of the upper and lower rings,height of the platform,mass center of the load,spring stiffness and some other factors as the variables,is built.Four groups of variables with relatively high correlation were selected to analyze their combined impact on the optimization goals.Furthermore,the non-dominated sorting genetic algorithm NSGA-Ⅱ is applied to find the optimal structural parameters.Finally,the comparative analysis of examples shows that the overall performance of the optimized platform is significantly improved.
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