基于卷烟包装纸挥发性有机化合物(VOCs)含量运用电子鼻系统构建的快速品质判别技术

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• 英文论文题名：Rapid Quality Discriminant technology base on Volatile 0rganic Compounds(VOCs) in Cigarette Packaging Papers using Electronic Nose System
• 论文作者：吴君章 ; 孔浩辉 ; 郭伟清 ; 甘峰
• 年：2016
• 作者机构：广东中烟工业有限责任公司;中山大学化学与化工学院;
• 论文关键词：电子鼻 ; 卷烟包装纸 ; VOCs ; 品质判别
• 英文论文关键词：electronic nose ; cigarette packing paper ; VOCs ; quality discrimination
• 会议召开时间：2016-12-01
• 会议录名称：中国烟草学会2016年度优秀论文汇编——烟草工业主题
• 语种：中文
• 分类号：TS761.2
• 学会代码：ZGYG
• 学会名称：中国烟草学会
• 页数：13
• 文件大小：535k
• 原文格式：D

摘要

本文结合卷烟包装纸挥发性有机化合物(VOCs)含量和电子鼻检测结果,用DFA、PCA、SIMCA、PARAFAC和PARAFAC2共5种方法分别构建苯含量判别模型和15种VOCs总含量判别模型。对比5种方法的建模结果,发现采用DFA构建苯含量判别模型,以及采用DFA或SIMCA构建15种VOCs总含量判别模型,可较好地实现卷烟包装纸品质的快速判别。
In our study, we combined the response of electronic nose system and the content of volatile organic compounds(VOCs) in he cigarette packing paper, using DFA,PCA, SIMCA, PARAFAC and PARAFAC2 algorithms, to construct benzene content discriminant model and 15 kinds VOCs discriminant model. The results of 5methods were compared, and it was found that we could get better rapid quality discriminations when using DFA algorithm to construct benzene content discriminant model and using DFA or SIMCA algorithm to construct 15 kinds VOCs discriminant model.

引文

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