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|Type:||Artigo de periódico|
|Title:||Determination of API gravity, kinematic viscosity and water content in petroleum by ATR-FTIR spectroscopy and multivariate calibration|
|Abstract:||In this work, API gravity, kinematic viscosity and water content were determined in petroleum oil using Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR). Support vector regression (SVR) was used as the non-linear multivariate calibration procedure and partial least squares regression (PLS) as the linear procedure. In SVR models, the multiplication of the spectra matrix by support vectors resulted in information about the importance of the original variables. The most important variables in PLS models were attained by regression coefficients. For API gravity and kinematic viscosity these variables correspond to vibrations around 2900 cm(-1), 1450 cm(-1) and below to 720 cm(-1) and for water content, between 3200 and 3650 cm(-1), around 1650 cm(-1) and below to 900 cm(-1). The SVR model produced a root mean square error of prediction (RMSEP) of 0.25 for API gravity, 22 mm(2) s(-1) for kinematic viscosity and 0.26% v/v for water content. For PLS models, the RMSEP values for API gravity was 0.38 mm(2) s(-1), for kinematic viscosity was 27 mm(2) s(-1) and for water content was 0.34%. Using the F-test at 95% of confidence it was concluded that the SVR model produced better results than PLS for API gravity determination. For kinematic viscosity and water content the two methods were equivalent. However, a non-linear behavior in the PLS kinematic viscosity model was observed. (C) 2013 Elsevier Ltd. All rights reserved.|
Partial least squares regression
Support vector regression
|Editor:||Elsevier Sci Ltd|
|Citation:||Fuel. Elsevier Sci Ltd, v. 116, n. 123, n. 130, 2014.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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