摘要
利用固相微萃取-气质联用(SPME-GC-MS)技术,对汽油、柴油、聚苯乙烯、ABS 4种石化燃料进行燃烧烟尘的特征组分分析,对其特征组分谱图中的保留时间进行归纳总结。对获得的20×35的数学矩阵,进行了主成分分析,得到了3个主成分,其累计率达到了92%,表明主成分所组成的二维数学坐标以及三维坐标系能较好地将不同比例的烟尘进行分类。最后在主成分分析的基础上,应用高级模式识别方法系统聚类方法,以100%的精确度将四类不同来源的燃料烟尘归类分开。
The SPME-GC-MS method is applied to analyze the characteristic components of combustion soot generated by four kinds of petroleum chemicals fuels i. e. the gasoline, the diesel, the polystyrene and the ABS （acrylonitrile butadiene styrene）. The spectrums of these four different combustion soot and the corresponding characteristic components are obtained by this method. Based on the retention time and the corresponding characteristic components summarized from the spectrums of the four kinds of combustion soot, a 20× 35 mathematic matrix is obtained. The PCA method is applied to analyze this matrix and in succession three main principal components are summarized, with the cumulative rate up to 92%, which indicates that the two or three dimensional coordinate system composed of the principal components is quite effective to classify the combustion soot of different fuels. Finally, based on the results of PCA, an advanced pattern recognition method i. e. the HCA is applied to classify the four types of combustion soot with 100% accuracy.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2011年第12期3595-3600,共6页
CIESC Journal
基金
国家自然科学基金项目(50974110)
苏州市科技计划项目(SYJG0911)
“十二五”科技支撑计划项目(2011BAK07B01-02)~~
关键词
石化燃料
聚苯乙烯
模式识别
燃烧烟尘
petroleum chemicals fuels
polystyrene
pattern recognition
combustion soot
作者简介
支有冉（1984-），男，博士研究生。
联系人：宗若雯。
