Gasoline classification by source and type based on near infrared (NIR) spectroscopy data

被引：127
作者：
Balabin, Roman M. [1 ]
Safieva, Ravilya Z. [1 ]
机构：
[1] Gubkin Russian State Univ Oil & Gas, Moscow 119991, Russia
来源：
FUEL | 2008年 / 87卷 / 07期
关键词：
gasoline; classification; near infrared (NIR) spectroscopy;
D O I：
10.1016/j.fuel.2007.07.018
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
In this paper, we have tried to classify 382 samples of gasoline and gasoline fractions by source (refinery or process) and type. Three sets of near infrared (NIR) spectra (450, 415, and 345 spectra) were used for classification of gasolines into 3 or 6 classes. We have compared the abilities of three different classification methods: linear discriminant analysis (LDA), soft independent modeling of class analogy (SIMCA), and multilayer perceptron (MLP) - to build effective and robust classification model. In all cases NIR spectroscopy was found to be effective for gasoline classification purposes. MLP technique was found to be the most effective method of classification model building. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1096 / 1101
页数：6
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