基于BP神经网络的聚丙烯/氢氧化镁复合材料阻燃性能预测模型  

Flame Retardancy Prediction Model for Polypropylene/Magnesium Hydroxide Composites Based on BP Neural Network

作　　者：曾书航 王泽艳 李智力[1] 廖杰 李嘉霖 何东升[1] 唐远 付艳红 ZENG Shu-hang;WANG Ze-yan;LI Zhi-li;LIAO Jie;LI Jia-lin;HE Dong-sheng;TANG Yuan;FU Yan-hong(School of Resources and Safety Engineering,Wuhan Institute of Technology,Wuhan 430073,China;Hubei Jinchu Dye Intermediate Industry Technology Research Institute Co.,Ltd.,Jingzhou 434400,China;Liangxin College,China Jiliang University,Hangzhou 310018,China)

机构地区：[1]武汉工程大学资源与安全工程学院,湖北武汉430073 [2]湖北金楚染料中间体产业技术研究院有限公司,湖北荆州434400 [3]中国计量大学量新学院,浙江杭州310018

出　　处：《塑料科技》2024年第5期18-22,共5页Plastics Science and Technology

基　　金：湖北省高等学校优秀中青年科技创新团队计划项目(T2021006);湖北省科技计划项目重点研发专项(2023BCB076);武汉市知识创新专项曙光计划项目(2022020801020356);武汉工程大学大学生校长基金项目(XZJJ2023052)。

摘　　要：为预测和提高聚丙烯/氢氧化镁(PP/MH)复合材料的阻燃性能,掌握不同因素对材料阻燃性能的影响强度,以MH粒径、接触角、添加量为3个输入量,以PP/MH复合材料的极限氧指数(LOI)为输出量,建立3层BP神经网络预测模型,将正交试验结果作为样本对其进行训练,用于预测复合材料的阻燃性能,设计实验对预测结果进行验证。结果表明:各因素对材料阻燃性能的影响由大到小依次为MH添加量、MH接触角和MH粒径。最佳的工艺参数:MH粒径为0.2μm、MH接触角为135°、MH添加量为40%,此条件下PP/MH复合材料的LOI高达31.5%。该BP神经网络模型能够准确预测复合材料的阻燃性能,预测值和试验值的相对误差一般小于5%。建立的阻燃性能预测模型可用于材料的性能优化,可减少实验工作量,提高工作效率。In order to improve the flame retardancy of polypropylene/magnesium hydroxide(PP/MH)composites and to grasp the intensity of different influencing factors on the flame retardancy of the materials,the MH particle size,contact angle,and the amount of additive were used as the three inputs,and the limiting oxygen index(LOI)of PP/MH composites was taken as the output.A three-layer BP neural network prediction model was established,and the orthogonal test results were used as samples to train it to predict the flame retardancy of the composites.The prediction results were verified by experiments.The results show that the effects of various factors on the flame retardancy of the PP/MH composites from large to small are MH content,MH contact angle and MH particle size.The optimal process parameters:the MH particle size is 0.2μm,the MH contact angle is 135°,the MH content is 40%.Under these conditions,the LOI of PP/MH composite is as high as 31.5%.The BP neural network model can accurately predict the flame retardancy of composites,and the relative error between the predicted value and the experimental value is generally less than 5%.The prediction model of flame retardancy can be used to optimize the performance of materials,reduce the experimental workload,and improve the work efficiency.

关 键 词：BP神经网络 聚丙烯 氢氧化镁 硬脂酸钠 阻燃性能 

分 类 号：TB33[一般工业技术—材料科学与工程]