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基于NSGA-Ⅱ遗传算法的低比转速离心泵多目标寻优
引用本文:赵伟国,夏添,省袁志,李尚升.基于NSGA-Ⅱ遗传算法的低比转速离心泵多目标寻优[J].兰州理工大学学报,2020,46(4):55.
作者姓名:赵伟国  夏添  省袁志  李尚升
作者单位:1.兰州理工大学 能源与动力工程学院, 甘肃 兰州 730050;
2.兰州理工大学 甘肃省流体机械及系统重点实验室, 甘肃 兰州 730050;
3.宁波沃力科技有限公司, 浙江 宁波 315000
基金项目:国家自然科学基金(51269011)
摘    要:为了提高低比转速离心泵的水力效率和扬程,选取比转速为30的某一低比转速离心泵为研究对象,以离心泵的扬程和水力效率最大值作为优化目标,采用离心泵基本方程与Plackeet-Burman试验相结合的方法进行参数筛选,最终选取离心泵叶轮的叶片出口安放角、叶片包角和叶片出口宽度作为优化变量.在优化过程中,采用最优拉丁超立方设计方法安排了30组试验,利用RBF神经网络模型拟合出优化目标与变量之间的近似模型,并运用基于NSGA-Ⅱ遗传算法进行多目标寻优.优化结果表明:优化后的叶轮扬程基本没有变化,水力效率提高了5.82%,消除了流量-扬程曲线的驼峰现象,使离心泵的运行更加稳定;优化后叶轮流道内的压力梯度减小,漩涡的发生区域及大小也有不同程度的改善;叶轮流道内湍流区域分布均匀,叶片做功能力增强,水力效率得到提高.

关 键 词:离心泵  低比转速  扬程  水力效率  
收稿时间:2018-05-04

Multi-objective parameters optimization of low specific speed centrifugal pump based on NSGA-Ⅱ genetic algorithm
ZHAO Wei-guo,XIA Tian,SHENG Yuan-zhi,LI Shang-sheng.Multi-objective parameters optimization of low specific speed centrifugal pump based on NSGA-Ⅱ genetic algorithm[J].Journal of Lanzhou University of Technology,2020,46(4):55.
Authors:ZHAO Wei-guo  XIA Tian  SHENG Yuan-zhi  LI Shang-sheng
Institution:1. College of Energy and Power Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China;
2. Key Laboratory of Fluid Machinery and Systems of Gansu Province, Lanzhou Univ. of Tech., Lanzhou 730050, China;
3. MARQUIS Co., Ltd., Ningbo 315000, China
Abstract:In order to improve hydraulic efficiency and head of a low specific-speed centrifugal pump, a low specific-speed centrifugal pump with 30 specific-speed was selected as a research object in this study. By taking the maximum head and hydraulic efficiency of centrifugal pump as two optimization objectives, the basic equation of centrifugal pump and the Plackeet-Burman test are combined for screening parameters to be optimized. By doing so. the vane outlet placement angle of centrifugal pump impeller was selected, and the wrap angle and outlet width of the blades were selected too as variables for optimization in our study. In the optimization process, 30 groups of experiments were arranged using the optimal Latin super-cubic design method, and then an approximate model between the optimization target and the variables was fitted numerically by using the RBF neural network model. The multi-objective optimization was finally carried out in terms of NSGA-Ⅱ genetic algorithm. The optimization results show that the head of the optimized impeller basically remains unchanged, the hydraulic efficiency of the impeller is 5.82% higher than that before optimization. The optimization eliminates the hump on the flow-head curve of the impeller and makes the operation of the centrifugal pump more stable. The pressure gradient in the impeller flow channel is reduced after optimization, and the area as well as size of eddies are reduced apparently to some extent. The turbulence area in the impeller flow channel becomes uniformly distributed, and blades to work are enhanced as a result. Thus the hydraulic efficiency has been improved.
Keywords:centrifugal pumps  low specific speed  head  hydraulic efficiency  
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