|本期目录/Table of Contents|

[1]禹新良,柳 俊.支持向量机在丁苯橡胶合成及加工中的应用[J].合成橡胶工业,2022,5:365-369.
　YU Xin-Liang,LIU Jun.Application of support vector machine in synthesis and processing of butadiene-styrene rubber[J].China synthetic rubber industy,2022,5:365-369.
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支持向量机在丁苯橡胶合成及加工中的应用(PDF)

《合成橡胶工业》[ISSN:1000-1255/CN:62-1036/TQ]

期数:
2022年5期
页码:
365-369
栏目:
出版日期:
2022-09-15

文章信息/Info

Title:
Application of support vector machine in synthesis and processing of butadiene-styrene rubber
文章编号:
1000-1255（2022）05-0365-05
作者:
禹新良; 柳 俊
湖南工程学院 材料与化工学院， 湖南 湘潭 411104
Author(s):
YU Xin-Liang;  LIU Jun
College of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China
关键词:
丁苯橡胶; 支持向量机; 乳液聚合; 硫化工艺; 炭黑用量
Keywords:
butadiene-styrene rubber;  support vector machine;  emulsion polymerization;  vulcanization process;  carbon black amount
分类号:
TQ 333.1
DOI:
DOI:10.19908/j.cnki.ISSN1000-1255.2022.05.0365
文献标识码:
A
摘要:
采用支持向量机（SVM）与粒子群寻优算法，建立了丁苯橡胶SBR 1712聚合过程和硫化工艺的模拟模型。结果表明，以SBR 1712产品性能胶乳固含量、门尼黏度和分子量分布系数作为输入，乳液间歇聚合所采用的引发剂、活化剂、链转移剂用量分别作为输出的预测模型，训练集及测试集的决定系数均大于0.8，模型预测值与实验值相吻合。以SBR 1712硫化加工中产品的邵尔A硬度、焦烧时间、最小弹性转矩、最小黏性转矩作为输入变量，建立了以填料炭黑用量作为输出的SVM模型，模型拟合及预测性能效果较好。
Abstract:
Prediction models were established for the polymerization and vulcanization process of butadiene-styrene rubber SBR 1712, by applying support vector machine (SVM) and particle swarm optimization algorithms. The results showed that the models with the solid content, Mooney viscosity and molecular weight polydispersity of SBR 1712 as inputs and the amount of initiator, activator and chain transfer agent used in batch emulsion polymerization as outputs produced determination coefficients greater than 0.8 for the training and test sets, and the predicted values from the models were consistent with the experimental values. Another SVM model was developed by using loading amount of furnace carbon black as output parameter and the properties in vulcanization process as input variables, including the shore A hardness, scorch time, minimum elastic torque and minimum viscous torque of SBR 1712. This model had excellent performance in fitting and prediction.

参考文献/References

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备注/Memo

备注/Memo:
湖南省自然科学基金资助项目(12 JJ 6011)。
更新日期/Last Update: 2022-09-15