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基于改进的BP-NSGAⅡ算法的注塑工艺参数优化
英文标题:Optimization on injection process parameters based on an improved BP-NSGA Ⅱ algorithm
作者:曹志勇 幸俊龙 夏巨谌 王新云 
单位:华中科技大学 湖北大学 
关键词:注塑工艺 Pareto最优解 正交试验 BP神经网络 NSGAⅡ算法 
分类号:TG309
出版年,卷(期):页码:2016,41(11):135-142
摘要:
注塑成形工艺优化的目标就是要在设备固定、原料配方不变的情况下,将保证质量和提高效率两者协调一致,以达到最理想的成形工艺。首先建立了以产品质量和生产效率为目标函数,以模具温度、熔体温度、保压压力、保压时间和冷却时间等为决策变量的多目标综合优化模型。利用BP神经网络的强大的非线性插值能力和自我学习能力来训练模型样本数据,最后结合改进的非支配排序遗传算法(NSGAⅡ)的全局寻优和多目标优化求解能力,得出最优的注塑工艺设计。

The goal of the optimization on injection molding process is to ensure both the quality and efficiency under remaining equipment and materials to achieve the ideal forming process. Firstly, the objective function with quality and efficiency was confirmed, then the integrated optimization model was constructed with multi-objective decision variables of mold temperature, melt temperature, packing pressure, dwell time and cooling time. Furthermore, the sample data of model were trained by the powerful non-linear interpolation and self-learning ability of BP network. In the end, the optimal injection designing process was obtained by combining the global and multi-objection optimization ability of the improved Non-dominated Sorting Genetic AlgorithmsⅡ.

基金项目:
国家自然科学基金青年项目(51205144)
作者简介:
曹志勇(1972-),男,博士研究生 王新云(1973-),男,博士,教授
参考文献:


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