Development of a SIMCA model for classification of kerosene by infrared spectroscopy

Autor:	Ángel Dago Morales, Reinaldo Fernández Fernández, Alberto Cavado Osorio, Ernesto Linchenat Dennes
Rok vydání:	2008
Předmět:	SIMCA model business.industry kerosene classification Mineralogy Pattern recognition General Chemistry Artificial intelligence infrared spectroscopy business Mathematics
Zdroj:	Química Nova, Volume: 31, Issue: 6, Pages: 1573-1576, Published: 2008 Química Nova v.31 n.6 2008 Química Nova Sociedade Brasileira de Química (SBQ) instacron:SBQ
ISSN:	0100-4042
Popis:	In the petroleum refining industry, the use of crude from several origins is frequent. This leads to a product of variable chemical composition during refining, hindering quality control. Therefore, it is important to develop classification models that help to better characterize those products. The objective of this study is to develop a SIMCA recognition pattern to classify kerosene using infrared spectroscopy data. The model permits to differentiate two kerosene groups with different chemical compositions, which was corroborated by mass spectrometry.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f1cadf351e9ff9f2b6e4d99c50bf2e6 https://doi.org/10.1590/s0100-40422008000600049 Zobrazit plný text záznamu