往复泵进液阀阀球运动特性研究及多目标优化  

Research on valve ball motion characteristics and multi-objective optimization of reciprocating pump inlet valve

作　　者：丁啸 沈叶辉 陈德泉 周邵萍[1] DING Xiao;SHEN Yehui;CHEN Dequan;ZHOU Shaoping(Key Laboratory of Pressurized Systems and Safety,Ministry of Education,East China University of Science and Technology,Shanghai200237,China;Shanghai First Fluid Machine Co.Ltd.,Shanghai201700,China)

机构地区：[1]华东理工大学承压系统与安全教育部重点实验室,上海200237 [2]上海福思特流体机械有限公司,上海201709

出　　处：《流体机械》2024年第5期55-63,70,共10页Fluid Machinery

基　　金：国家重点研发计划项目(2016YFF0203301)。

摘　　要：为了研究往复泵泵阀内阀球运动特性并优化其性能,借助动网格及UDF技术,对往复泵进液过程中阀球运动与泵阀流场进行耦合计算和试验验证,得到阀球运动规律,并分析阀球质量、阀导套导流孔结构以及阀套限位高度等对泵阀运动及性能的影响。为进一步优化模型,寻找到最优泵阀结构组合方案,提出构建径向基神经网络(RBFNN)代理模型,借助多目标粒子群(MOPSO)算法得到其Pareto最优解集的优化框架并验证分析。结果表明:阀球运动升程整体呈现先增大后减小的变化规律,受阀隙流速和液动力影响很大;阀球质量、阀导套导流孔对数以及阀套限位高度等与阀球最大升程和落座速度均存在非线性关系;基于RBFNN代理模型结合MOPSO算法寻找到最优组合模型,优化后阀球最大升程提高了8.12 mm,阀球落座速度减小了31.4%,优化效果显著。研究结果可为往复泵的优化设计提供参考。In order to study the motion characteristics of the valve ball in the reciprocating pump valve and optimize its performance,the dynamic grid and UDF technology were used to conduct the calculation of coupling between the valve ball motion and the flow field of the pump valve and experimental verification during the liquid inlet process of the reciprocating pump,so as to obtain the motion law of the valve ball,and analyze the influences of the valve ball mass,the guide hole structure of the valve guide sleeve and the limit height of the valve sleeve on the valve movement and performance.In order to further optimize the model and find the optimal combination scheme of pump and valve structure,the radial basis neural network(RBFNN)proxy model was proposed and the optimization framework of its Pareto optimal solution set was obtained by multi-objective particle swarm(MOPSO)algorithm and was verified.The results show that the motion lift of valve ball increases first and then decreases,which is greatly affected by the flow rate of valve gap and hydrodynamic force.The mass of valve ball,the number of valve guide holes and the limit height of valve sleeve have nonlinear relationship with the maximum lift and seating speed of valve ball.Based on the RBFNN proxy model and MOPSO algorithm,the optimal combination model was found.After optimization,the maximum lift of the valve ball was increased by 8.12 mm,and the seating speed of the valve ball was reduced by 31.4%.The optimization effect was remarkable.The research results can provide reference for the optimization design of reciprocating pumps.

关 键 词：数值模拟 动网格 UDF RBFNN代理模型 MOPSO算法 

分 类 号：TH3[机械工程—机械制造及自动化]