基于蜂群算法的等压灌装阀阀口流道结构优化

发布时间：2018-04-06 23:36

本文选题：等压灌装阀　切入点：阀口流道　出处：《包装工程》2017年23期

【摘要】：目的为了改善等压灌装阀的灌装性能,分析阀口流道结构参数对液料流场的影响,求解流道内最大压力损失、最大液料流速和最大湍动能均最小化的约束多目标优化问题。方法基于正交试验设计和Fluent流场仿真软件对灌装阀阀口流道流场进行数值模拟,并通过回归分析建立以阀口流道结构参数为自变量的最大压力损失、最大液料流速和最大湍动能的经验方程,进而建立阀口流道结构参数约束多目标优化模型,采用约束多目标人工蜂群算法对优化模型进行求解。结果流道内最大压力损失最小化、最大液料流速最小化和最大湍动能最小化这3个目标之间存在冲突,无法同时达到最优,基于多目标人工蜂群算法获得了阀口流道结构参数的最优Pareto解集。结论约束多目标人工蜂群算法能有效用于等压灌装阀阀口流道结构参数的优化。
[Abstract]:Aim in order to improve the filling performance of the constant pressure filling valve, the influence of the structure parameters of the valve orifice on the flow field is analyzed, and the constrained multi-objective optimization problem with the maximum pressure loss, the minimization of the maximum flow velocity and the maximum turbulent kinetic energy in the flow channel is solved.Methods based on orthogonal test design and Fluent software, the flow field of filling valve outlet was numerically simulated, and the maximum pressure loss was established by regression analysis.Based on the empirical equations of maximum liquid flow velocity and maximum turbulent kinetic energy, a multi-objective optimization model with constrained multi-objective artificial bee colony algorithm is established.Results the maximum pressure loss, the maximum flow velocity minimization and the maximum turbulent kinetic energy minimization of the three objectives in the flow channel are in conflict, and the maximum flow velocity and the maximum turbulent kinetic energy can not reach the optimum at the same time.Based on multi-objective artificial bee colony algorithm, the optimal Pareto solution set of valve runner structure parameters is obtained.Conclusion the constrained multi-objective artificial bee colony algorithm can be used to optimize the structure parameters of the orifice of the constant pressure filling valve.
【作者单位】：北京工商大学;
【基金】：北京市教育委员会科技发展计划面上项目(KM201510011005) 北京工商大学两科基金(19008001273)
【分类号】：TB486;TP18

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