何新波, 方伟, 韩勇, 周瑜, 班晓娟, 曲选辉. 基于人工神经网络的粉末注射成形智能化控制仿真系统[J]. 工程科学学报, 2011, 33(5): 623-626. DOI: 10.13374/j.issn1001-053x.2011.05.019
引用本文: 何新波, 方伟, 韩勇, 周瑜, 班晓娟, 曲选辉. 基于人工神经网络的粉末注射成形智能化控制仿真系统[J]. 工程科学学报, 2011, 33(5): 623-626. DOI: 10.13374/j.issn1001-053x.2011.05.019
HE Xin-bo, FANG Wei, HAN Yong, ZHOU Yu, BAN Xiao-juan, QU Xuan-hui. Intelligent control simulation system for powder injection molding based on artificial neural network[J]. Chinese Journal of Engineering, 2011, 33(5): 623-626. DOI: 10.13374/j.issn1001-053x.2011.05.019
Citation: HE Xin-bo, FANG Wei, HAN Yong, ZHOU Yu, BAN Xiao-juan, QU Xuan-hui. Intelligent control simulation system for powder injection molding based on artificial neural network[J]. Chinese Journal of Engineering, 2011, 33(5): 623-626. DOI: 10.13374/j.issn1001-053x.2011.05.019

基于人工神经网络的粉末注射成形智能化控制仿真系统

Intelligent control simulation system for powder injection molding based on artificial neural network

  • 摘要: 基于数值模拟和人工神经网络模型以及对智能控制工艺过程的适当简化,为拉伸样模型的注射过程建立了一套智能化控制仿真系统.研究表明,该系统能够根据样品对性能的要求(如密度分布),自动进行注射工艺参数的优化.采用优化后的注射工艺参数重新进行注射过程模拟计算后,发现注射坯密度分布的均匀性较调整前有显著提高,基本符合预期的密度要求,证明智能化控制仿真系统可行.

     

    Abstract: Based on numerical calculations and an artificial neural network (ANN) model as well as intelligent control technology, a set of intelligent control simulation system was founded for the injection process of standard tensile samples. The results show that this system can automatically optimize injection parameters according to the requirement of injection bodies to the properties (such as density distribution). It is found, after the introduction of the intelligent control simulation system to injection processing, that the uniformity of density distribution in injection bodies is obviously improved and can meet the expected density distribution, proving that this intelligent control simulation system is feasible.

     

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