Provider: ingentaconnect
Database: ingentaconnect
Content: application/x-research-info-systems
TY - ABST
AU - Seasholtz, M. B.
AU - Archibald, D. D.
AU - Lorber, A.
AU - Kowalski, B. R.
TI - Quantitative Analysis of Liquid Fuel Mixtures with the Use of Fourier Transform Near-IR Raman Spectroscopy
JO - Applied Spectroscopy
PY - 1989-08-01T00:00:00///
VL - 43
IS - 6
SP - 1067
EP - 1072
KW - Liquid hydrocarbon analysis
KW - Spectroscopy (near-IR, Raman, FT-IR, quantitative)
KW - Partial least-squares
KW - Multivariate calibration
KW - Multiple linear regression
N2 - Near-infrared Fourier transform (near-IR FT) Raman spectroscopy was used to predict mass percentages of liquid fuel mixtures without the use of an internal standard. The 29 mixtures making up the calibration set were composed of varying mass percentages of unleaded gasoline, super-unleaded
gasoline, and diesel. Predictions were made with the use of classical least-squares with the pure components. Root mean square error (RMSE) values for all samples were 13.5, 13.8, and 5.2% (absolute error) for unleaded, superunleaded, and diesel, respectively. Using an estimate of the pure
spectra determined by calibration gave RMSE values of 13.3% for unleaded, 12.2% for superunleaded, and 5.0% for diesel. A partial least-squares (PLS) model was able to partially compensate for matrix effects. Using different portions of the Raman spectra reduced the RMSE to 5.7% for unleaded,
5.2% for superunleaded, and 1.3% for diesel.
UR - http://www.ingentaconnect.com/content/sas/sas/1989/00000043/00000006/art00028
M3 - doi:10.1366/0003702894203985
UR - http://dx.doi.org/10.1366/0003702894203985
ER -