Recursive PLS Modeling of Aromatics and Olefins in Gasoline

Jing Fang Wang

doi:10.4028/www.scientific.net/AMR.740.267

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 740Recursive PLS Modeling of Aromatics and Olefins in...

Recursive PLS Modeling of Aromatics and Olefins in Gasoline

Abstract:

The separate calibration models of aromatics and olefins were established for gasoline through recursive partial least square (R-PLS) method in this paper.The some oil refining enterprise application has achieved better effect on the software being realized by R-PLS method. The calibration models were validated through comparison of the results determined by fluorescent indicator adsorption (FIA) and near infrared spectroscopy (NIR) methods.The NIR analysis results were well coincident with those of FIA method.The NIR can not only raise the analysis efficiency and lower the analysis cost,but also has better precision compared with FIA method.

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Periodical:

Advanced Materials Research (Volume 740)

Pages:

267-272

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.740.267

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Online since:

August 2013

Authors:

Jing Fang Wang

Keywords:

Aromatic, Gasoline, Near Infrared Spectroscopy (NIRS), Olefin, Recursive Partial Least-Squares

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References

[1] GB / T 11132-2002 liquid petroleum products, hydrocarbons assay fluorescent indicator adsorption method [S].

Google Scholar

[2] SI-I / T 0741-2004 Gasoline Hydrocarbon Composition Determination multidimensional gas chromatography [s].

Google Scholar

[3] salicin. The near-infrared spectroscopy naphtha aromatics content model calibration study [J]. Infrared, 2007,28 (6) :33-37.

Google Scholar

[4] Xiao-Li Chu Yuan Hongfu, Ji Changqing. Near-infrared spectroscopy reforming gasoline ethnic composition [J]. Petrochemical, 2001,30 (11) :866-870.

Google Scholar

[5] Optimizing Li Guoliang, Lu Wanzhen. Near infrared spectroscopy distillation range of light oil and steam pressure [J]. Petroleum Processing and Petrochemicals, 2002,33 (5) :57-61.

Google Scholar

[6] Fanrui Jun, Wang Xuan-jun, Zhang Youzhi. Correction of near-infrared spectra of jet fuel analysis model [J]. Petroleum Processing and Petrochemicals, 2006, 37 (6) :57-61.

Google Scholar

[7] Feng the new Lu, Shi Yonggang. Near-infrared spectroscopy and its application in the analysis of petroleum products [M]. Beijing: China Petrochemical on Press,2002:150-158

Google Scholar

[8] Wold S, Trygg J, Berglund A, et a /. Some recent developments in PLSmodeling [J]. Chemometrics and Intelligent Laboratory Systems, 2001,58:131 - 150．

DOI: 10.1016/s0169-7439(01)00156-3

Google Scholar