BP神经网络在POE-g-MAH/HDPE增韧PA6研究中的应用  

Application of BP Neural Network to POE-g-MAH/HDPE Toughening PA6

作　　者：陈坤[1] 郑梯和[1] 宋克东[1] 田祥儒[1] 张瑜[1] 邓如生[1] 

机构地区：[1]株洲时代新材料科技股份有限公司,湖南株洲412007

出　　处：《塑料工业》2011年第8期45-47,80,共4页China Plastics Industry

摘　　要：运用BP神经网络研究了马来酸酐接枝乙烯-辛烯共聚物(POE-g-MAH)/高密度聚乙烯(HDPE)对尼龙6(PA6)的增韧作用,并在此基础上建立了PA6/POE-g-MAH/HDPE复合材料各组分用量与复合材料冲击强度的关系模型。结果表明:该模型和实验结果基本吻合,可信度较高;当POE-g-MAH质量分数为12%,HDPE质量分数为16%时,PA6的缺口冲击强度达到95.02 kJ/m2。The research of POE-g-MAH/HDPE toughening PA6 was conducted by BP neural network in this paper and on this basis, relational model for composite between impact strength and the composition was established. The results showed that the relational model had high credibility which agreed well with the experiments. The impact strength of the toughening nylon6 reached at 95.02 kJ/m2 when the content of POE-g- MAH was 12 wt% and HDPE content was 16 wt%.

关 键 词：神经网络 增韧 尼龙6 高密度聚乙烯 

分 类 号：TQ327[化学工程—合成树脂塑料工业]