Determination of multi-properties of residual oils using mid-infrared attenuated total reflection spectroscopy

被引:44
作者
Yuan Hongfu [1 ]
Chu Xiaoli [1 ]
Li Haoran [1 ]
Xu Yupeng [1 ]
机构
[1] Res Inst Petr Proc, Analyt Dept, Beijing 100083, Peoples R China
关键词
mid-infrared; partial least square; classification;
D O I
10.1016/j.fuel.2006.02.003
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
Several physical and chemical parameters (such as saturates, aromatics, resins, and asphaltenes, element contents, density, viscosity, and carbon residue) are necessary to characterize residual oils. The combined use of mid-infrared (MIR) attenuated total reflection (ATR) spectroscopy and multivariate calibration allows those parameters to be estimated accurately. In order to improve the prediction results, samples from different processing units require different calibration models relative to the spectral similarities. This paper builds a strategy to classify and discriminate different types of residual oils by use of partial least square regression. The calibration models for the physical and chemical parameters of three types of residual oils were developed, respectively. The consistencies between the MIR predicted and reference values testify to the creditability of the proposed method. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1720 / 1728
页数:9
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