Sage Journals: Discover world-class research

Abstract

A new genetic algorithm is presented for sensor selection, in order to predict the octane number and the content of benzene, toluene and total aromatics in gasolines, based on partial least squares multivariate calibration of near infrared spectral data. The algorithm separately labels each of the selected wavenumber ranges with a relative inclusion ranking. Relative prediction errors (% of root mean square error with respect to the mean calibration value) achieved after sensor selection are: octane number, 0.5%, benzene, 0.6%, toluene, 0.6%, and total aromatics, 1.1%. The results are compared with those provided by the spark-ignition engine fuel research method for octane number and by gas chromatography for the remaining parameters.

Keywords

near infrared spectroscopy gasoline analysis wavenumber selection genetic algorithm multivariate calibration partial least squares

Get full access to this article

View all access options for this article.

References

ASTM Test Method D5769–98, Annual Book of ASTM Standards, Vol. 05.03. ASTM, West Conshohocken, PA, USA.

Burns

D.A.

and Ciurczak

E.W.

, Handbook of Near-Infrared Analysis. Marcel Dekker Inc., New York, NY, USA (1992).

Kelly

J.J.

Barlow

C.H.

Jinguji

T.M.

and Callis

J.B.

, Anal. Chem. 61, 313 (1989).

Bohács

Ovádi

and Salgó

, J. Near Infrared Spectrosc. 6, 341 (1998).

Chung

Lee

and Jun

C.-H.

, Bull. Korean Chem. Soc. 22, 37 (2001).

Martens

and Naes

, Multivariate Calibration. John Wiley and Sons, Chichester, UK (1989).

Bangalore

A.S.

Shaffer

R.E.

Small

G.W.

and Arnold

M.A.

, Anal. Chem. 68, 4200 (1996).

McShane

M.J.

Cote

G.L.

and Spiegelman

C.H.

, Appl. Spectrosc. 51, 1559 (1997).

Spiegelman

C.H.

McShane

M.J.

Goetz

M.J.

Motamedi

Yue

Q.L.

and Cote

G.L.

, Anal. Chem. 70, 35 (1998).

10.

Jiang

J.H.

Berry

R.J.

Siesler

H.W.

and Ozaki

, Anal. Chem. 74, 3555 (2002).

11.

Collado

M.S.

Mantovani

V.E.

Goicoechea

H.C.

and Olivieri

A.C.

, Talanta 52, 909 (2000).

12.

Goicoechea

H.C.

and Olivieri

A.C.

, Analyst 124, 725 (1999).

13.

Ding

Small

G.W.

and Arnold

M.A.

, Anal. Chem. 70, 4472 (1998).

14.

Swierenga

Wülfert

de Noord

O.E.

de Weijer

A.P.

Smilde

A.K.

and Buydens

L.M.C.

, Anal. Chim. Acta 411, 121 (2000).

15.

Todeschini

Galvani

Vilchez

J.L.

del Olmo

and Navas

, Trends Anal. Chem. 18, 93 (1999).

16.

Leardi

, J. Chemometr. 15, 559 (2001).

17.

Ferré

and Rius

F.X.

, Anal. Chem. 70, 1999 (1998).

18.

Araújo

Ugulino M.C.

Saldanha

Bezerra T.C.

Galvão

Harrop R.K.

Yoneyama

Chame

Caldas H.

and Visani

, Chemometr. Intell. Lab. Syst. 57, 65 (2001) and references therein.

19.

Davis

, Genetic Algorithm and Simulated Annealing. Pitman, London, UK (1987).

20.

Goldberg

D.E.

, Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, MA, USA (1988).

21.

Shaffer

R.E.

and Small

G.W.

, Anal. Chem. 69, 236A (1997).

22.

Goicoechea

H.C.

and Olivieri

A.C.

, J. Chem. Inf. Comp. Sci. 42, 1146 (2002).

23.

Goicoechea

H.C.

and Olivieri

A.C.

, J. Chemometr. (in press).

24.

ASTM Method D 2699–99 , Annual Book of ASTM Standards, Vol. 05.05. ASTM, West Conshohocken, PA, USA.

25.

Sanders

W.N.

and Maynard

J.B.

, Anal. Chem. 40, 527 (1968).

26.

Matlab, Version 6.0. The Math Works Inc., MA, USA (2000).

27.

Isaksson

and Naes

, Appl. Spectrosc. 42, 1273 (1988).

28.

Naes

Isaksson

and Kowalski

, Anal. Chem. 62, 664 (1990).

29.

Haaland

D.M.

and Thomas

E.V.

, Anal. Chem. 60, 1193 (1988).

30.

Faber

and Kowalski

B.R.

, Appl. Spectrosc. 51, 660 (1997).

31.

Goicoechea

H. C.

and Olivieri

A. C.

, Trends Anal. Chem. 19, 599 (2000).

A New Genetic Algorithm Applied to the near Infrared Analysis of Gasolines

Abstract

Keywords

Get full access to this article

References