双盘转子系统优化算法与试验  

Optimization algorithm and experiment of a two-disk rotor system

作　　者：黄晶晶[1] 郑龙席[1] 刘钢旗[1] 梅庆[2] 

机构地区：[1]西北工业大学动力与能源学院,西安710072 [2]中国航空工业集团公司中国航空动力机械研究所航空发动机振动技术航空科技重点实验室,湖南株洲412002

出　　处：《航空动力学报》2016年第1期65-71,共7页Journal of Aerospace Power

基　　金：航空科学基金(20112153019)

摘　　要：为了讨论不同优化算法的效果差异,利用有限元分析技术,针对典型1-0-1支承方案的双盘转子系统进行建模仿真,在分析其动力学特性的基础上,联合多学科优化软件ISIGHT,将两转盘位置作为优化变量,以1阶临界转速在10%内的变化为约束条件,采用不同的优化算法:进化算法(EVOL)、多岛遗传算法(MIGA)、邻域培植遗传算法(NCGA)、第二代非支配排序遗传算法(NSGA-Ⅱ)以及Pointer方法,最小化过1阶临界转速时两转盘的最大振幅,得到两转盘的最优位置.在高速柔性模拟转子试验器上进行了瞬态试验,结果表明,NSGA-Ⅱ只需要计算240个点,就可以使两转盘振幅分别下降76.94%和67.42%.因此,NSGA-Ⅱ是最适合该类转子系统的优化方法.In order to analyze the performance difference of several optimization algo- rithms, a model of two-disk rotor system with typical 1-0-1 support scheme was established and the dynamic characteristics were analysed by finite element analysis technology. On this basis, the two-disk rotor system model was integrated to the multidisciplinary design optimi- zation software ISIGHT. The positions of the two disks were selected as the optimization variables, the first order critical speed with the variation range of 10% was set as the con- straint, and the optimization objective was to minimize the amplitudes of the two disks cross- ing the first order critical speed with several different algorithms including evolutionary opti- mization （EVOL）, multi-island genetic algorithm （MIGA）, neighborhood cultivation genetic algorithm （NCGA）, non-dominated sorting genetic algorithm Ⅱ （NSGA-Ⅱ） and Pointer. The transient experiment was carried out on a high-speed flexible rotor mockup. Experimen- tal results indicated that NSGA-Ⅱmade the two disks＇ amplitudes decreased 76. 940/4 and 67.42% respectively with the calculation of 240 points. It can be concluded that NSGA-Ⅱ was the best optimization algorithm for the rotor system of this type.

关 键 词：双盘转子 优化算法 多目标优化 第二代非支配排序遗传算法 ISIGHT软件 

分 类 号：V231[航空宇航科学与技术—航空宇航推进理论与工程] O347.6[理学—固体力学]