中国塑料 ›› 2009, Vol. 23 ›› Issue (11): 69-74 .DOI: 10.19491/j.issn.1001-9278.2009.11.014

• 加工与应用 • 上一篇    下一篇

EVA塑料发泡倍率的实验研究与预测

许建文 刘斌 顾永华   

  1. 福建省泉州市华侨大学机电及自动化学院
  • 收稿日期:2009-07-06 修回日期:1900-01-01 出版日期:2009-11-26 发布日期:2009-11-26

Experimental Research and Prediction of Expansion Ratio of Foamed EVA Plastic

  

  • Received:2009-07-06 Revised:1900-01-01 Online:2009-11-26 Published:2009-11-26

摘要: 采用田口实验设计方法与BP(Back Propagation)神经网络技术,选取模具温度、模压时间、注射压力和模压压力四因素四水平安排正交实验,分析了工艺参数对EVA塑料发泡倍率的影响程度。结果发现,模具温度对发泡倍率的影响较为显著,模压时间次之,注射压力与模压压力的影响较小。最后选取对倍率影响较大的模具温度、模压时间与注射压力工艺参数,对不同形状与尺寸的标准试样模具安排正交实验,以实验结果作为神经网络的样本数据,经过训练后的神经网络能够较为准确地预测EVA塑料的发泡倍率。

关键词: 田口实验设计方法, BP神经网络, 乙烯-醋酸乙烯共聚物, 发泡倍率, 预测

Abstract: In the paper, adopt Taguchi DOE method and BP (Back Propagation) neural network technology, the effects of four factors, molding temperature, molding time, injection pressure, and molding pressure on the expansion ratio of EVA were studied with a four-level orthogonal experiment. It was concluded that the effect of molding temperature was the most obvious, that of molding time the second, and those of injection pressure and molding pressure are smaller. Taking molding temperature, molding time, and injection pressure as the parameters, another orthogonal experiment was carried out for different shapes and sizes of the standard sample molds. The experiment results were used as neural network sample data, and expansion ratio of EVA plastic could be predicted more accurately using after trained neural network.

Key words: Taguchi method of experimental design, Back Propagation neural network, ethylene-vinyl acetate copolymer, expansion ratio, prediction

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