A PLS regression model using flame spectroscopy emission for determination of octane numbers in gasoline

被引：36
作者：
de Paulo, Jaqueline M. [1 ]
Barros, Jose E. M. [2 ]
Barbeira, Paulo J. S. [1 ]
机构：
[1] Inst Ciencias Exatas, Dept Quim, Jose Do Rio Preto, Brazil
[2] Univ Fed Minas Gerais, Dept Engn Mecan, Escola Engn, Av Antonio Carlos 6627, BR-31270901 Belo Horizonte, MG, Brazil
来源：
FUEL | 2016年 / 176卷
关键词：
Octane numbers; Gasoline; PLS; Flame emission spectroscopy; LEAST-SQUARES REGRESSION; REID VAPOR-PRESSURE; PREDICTION;
D O I：
10.1016/j.fuel.2016.02.033
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：
This paper presents a method for the prediction of MON (Motor Octane Number) and RON (Research Octane Number) of automotive gasoline using flame emission spectroscopy and multivariate calibration (partial least squares). We obtained low values of RMSEC (root mean square error of calibration) and RMSEP (root mean square error of prediction), of 0.14 and 0.56, respectively for MON, while these values for RON were 0.34 and 0.9. The technique is simple and fast, does not require pretreatment of samples and still produces low octane rating errors, making it a good alternative to the standard method used in quality control of automotive gasoline. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码：216 / 221
页数：6
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