QUANTITATIVE GAS-ANALYSIS WITH FT-IR - METHOD FOR CO CALIBRATION USING PARTIAL LEAST-SQUARES WITH LINEARIZED DATA

被引:41
作者
BAK, J
LARSEN, A
机构
[1] KEMP & LAURITZEN,PROCESAUTOMAT,DK-2620 ALBERTSLUND,DENMARK
[2] RISO NATL LAB,DEPT COMBUST RES,DK-4000 ROSKILDE,DENMARK
关键词
QUANTITATIVE GAS ANALYSIS; FT-IR SPECTROSCOPY; MID-IR SPECTROSCOPY; MULTIVARIATE CALIBRATION; PLS MODELING; DATA LINEARIZATION;
D O I
10.1366/0003702953964237
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
Calibration spectra of CO in the 2.38-5100 ppm concentration range (22 spectra) have been measured with a spectral resolution of 4 cm(-1), in the mid-IR (2186-2001 cm(-1)) region, with a Fourier transform infrared (FT-IR) instrument. The multivariate calibration method partial least-squares (PLS1) was used to model the CO calibration spectra in order to improve the sensitivity and to flag possible outliers in the prediction step. The relation between the absorbance values and concentrations was strongly nonlinear. This result was caused mainly by the low spectral resolution of the instrument. To improve the model predictions, we have linearized the data prior to making the model calculations. The linearization scheme presented here simplified the data pretreatment, because the function needed to linearize the data might be approximated by co-absorbance peak areas representing the concentrations. The integrated absorbance areas, rather than the concentration values, were used as input to the PLS algorithm. A fifth-order polynomial was used to calculate the concentrations from the predicted absorbance areas. The PLS algorithm used on the linearized data reduced the number of factors in the calibration model. Our results reveal that the calibration model based on the linearized data had a high concentration prediction accuracy throughout the entire concentration range.
引用
收藏
页码:437 / 443
页数:7
相关论文
共 17 条
[1]   MULTIVARIATE DETERMINATION OF GLUCOSE IN WHOLE-BLOOD USING PARTIAL LEAST-SQUARES AND ARTIFICIAL NEURAL NETWORKS BASED ON MIDINFRARED SPECTROSCOPY [J].
BHANDARE, P ;
MENDELSON, Y ;
PEURA, RA ;
JANATSCH, G ;
KRUSEJARRES, JD ;
MARBACH, R ;
HEISE, HM .
APPLIED SPECTROSCOPY, 1993, 47 (08) :1214-1221
[2]   APPLICATION OF TG FT-IR TO STUDY HYDROCARBON STRUCTURE AND KINETICS [J].
CARANGELO, RM ;
SOLOMON, PR ;
GERSON, DJ .
FUEL, 1987, 66 (07) :960-967
[3]  
CROCOMBE RA, 1984, P ASTM S PHILADELPHI, P95
[4]   ACE - A NON-LINEAR REGRESSION-MODEL [J].
FRANK, IE ;
LANTERI, S .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1988, 3 (04) :301-313
[5]   NONLINEAR MULTIVARIATE CALIBRATION USING PRINCIPAL COMPONENTS REGRESSION AND ARTIFICIAL NEURAL NETWORKS [J].
GEMPERLINE, PJ ;
LONG, JR ;
GREGORIOU, VG .
ANALYTICAL CHEMISTRY, 1991, 63 (20) :2313-2323
[6]  
GIERCZAK CA, 1991, SPIE, V1433, P315
[7]  
HALLAND DM, 1988, ANAL CHEM, V60, P1193
[8]  
HALLAND DM, 1990, PRACTICAL FOURIER TR, P395
[9]  
IBURRA V, 1991, J ANAL APPL PYROL, V20, P185
[10]  
KOSCIELNIAK P, 1985, ANAL CHIM ACTA, V177, P197