Comparative Study of Diesel Analysis by Ftir, Ftnir and Ft-Raman Spectroscopy Using Pls and Artificial Neural Network Analysis

4975 Words Aug 31st, 2010 20 Pages
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Essay Sample: Page 2
[13] PLS RMSEP Calculated cetane index Density (kg/L) Viscosity (cSt) T50—boiling point at 50% recovery (◦ C) T85—boiling point at 85% recovery (◦ C) 1.3 0.0009 0.09 4 8e NIRf , ref. [26] PLS R2 Total sulfur (%, w/w)



NIRb , ref. [17] PCRc R2 0.991(4)d 0.992(2) 0.976(4) 0.975(4) RMSEP 0.7 0.002 0.19 4.9 PLS R2 0.985(3) 0.985(2) 0.979(2) 0.991(3) RMSEP 1.23 0.006 0.23 5.34

MLRg RMSEP 0.031 R2 0.895 RMSEP 0.022


Six hundred and eighty four samples used, 20% (137) were separated for validation. A horizontal ATR cell from Spectra-Tech 0012-436T was used. The authors have used two different instruments. The results presented in the table are those with the lowest RMSEP values. b One hundred and eighteen samples and 401 spectral points, ranging from 4000 to 13333 cm−1 . Thirty-three percent of the samples were separated for validation. There is one reference to the cetane number, for which the selected wavenumbers covered the range between 4000 and 4400 cm−1 . c PCR, principal component regression. d Values in parenthesis correspond to the number of factors or principal components. e The boiling point temperature at 90% recovery was property measured. f Ninety-seven samples: 41 samples for calibration, 30 for internal validation, and 26 for external validation. g MLR, multilinear regression.

regarding the use of Raman spectroscopy in the analysis of diesel. It is not
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