基于代理模型的注射参数迭代优化方法

Iterative optimization method for injection parameters based on surrogate model

型腔压力和熔体温差是反映塑料制品质量好坏的2项重要质量指标.考虑到塑料制品的薄壁特性,从黏性流体力学的基本方程出发,建立一种简化流动模型作为代理模型代替耗时的塑料注射成型模拟软件快速预测上述质量指标,基于代理模型的预测结果,采用粒子群算法实现注射参数的迭代优化,该方法计算速度快效率高,对知识的依赖程度低.最后通过实验对代理模型的正确性和优化方法的有效性进行验证,实验结果表明,基于代理模型的型腔压力预测值与实验值吻合较好,相对误差值只有8.41%,提出的优化方法与响应面方法的优化结果基本一致,但运行时间仅为响应面方法的0.02%.

Cavity pressure and temperature difference are two important quality criteria.Considering that most injection molded parts have a sheet like geometry,a fast strip analysis model based on mechanics equations for viscous fluid,was adopted as a surrogate model to approximate the time-consuming computer simulation software for predicating the above quality criteria.According to the predicted quality criteria,a particle swarm optimization algorithm was employed to find out the optimum injection parameters.The proposed optimization method can optimize the injection parameters in short time and it does not rely on any knowledge of molding process.Finally,two experiments were employed to validate the surrogate model and the proposed optimization method.Experimental results show that the cavity pressure predicted by the surrogate model agree well with the experimental data,with the relative error being less than 8.41%,and the results of the proposed optimization method are nearly identical to that of response surface method,while the required time of the proposed method is only 0.02% of that of response surface method.