Evaluation of Noisy Coherent Anti-Stokes Raman Spectra by Evolutionary Algorithms

  • U. Linnemann
  • P. Roosen
  • H.-J. Koß
Part of the Heat and Mass Transfer book series (HMT)


Coherent Anti-Stokes Raman Spectroscopy (CARS) is frequently the method of choice for non-intrusive temperature measurements in combustion systems. The temperature determination requires a comparison of measured spectra with theoretically calculated ones. Conventional gradient-based least squares fitting of experimental data with a library of theoretical spectra usually leads to sensible results, as long as the spectrum shapes behave well and the noise level is low.

The investigation of a 1 MW coal dust burner yielded only very noisy data that showed the limits of applicability of the gradient-based approach. Therefore in this paper a novel fitting approach based on evolutionary algorithms for such spectra is presented. The applied algorithm is explained. Temperature evaluation results, both conventionally and evolutionarily determined, are given.


Theoretical Spectrum Lorentz Width Line Width Parameter Coal Dust Burner Spontaneous Raman Spectroscopy 
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  1. R.J.H. Clark and R.E. Hester (ed.), Quantitative CARS spectroscopy, John Wiley & Sons Ltd., 1988.Google Scholar
  2. Y. Davidor, H.-P. Schwefel and R. Männer (ed.), Parallel Problem Solving from Nature — PPSN III, International Conference on Evolutionary Computation, Lecture Notes in Computer Science, vol. 866, Springer, Berlin, 1994.Google Scholar
  3. S. Druet and J.RE. Taran, Chemical and Biological Applications of Lasers (New York) (C.B. Moore, eds.), vol. 1, Academic Press, 1979.Google Scholar
  4. J. Klockgether and H.-R Schwefel, Two-Phase Nozzle and Hollow Core Jet Exper iments, 11th Symposium on Engineering Aspects of Magnetohydrodynamics (Pasadena, California), 1970.Google Scholar
  5. D.A. Long (eds.), Raman Spectroscopy, McGraw-Hill, 1977.Google Scholar
  6. R. Männer and B. Manderick (ed.), Parallel Problem Solving from Nature 2, Elsevier, Amsterdam, 1992.Google Scholar
  7. E. Peters and H.-R Schwefel, OptimiEst — An optimising expert system using topologies, Tech. Report 311, University of Dortmund, Department of Com puter Science, 1989.Google Scholar
  8. I. Rechenberg, Evolutionsstrategie: Optimierung technischer Systeme nach Prin zipien der biologischen Evolution, Frommann-Holzboog, Stuttgart, 1973.Google Scholar
  9. R Roosen, EPO V0.9a — The evolutionary parameter optimizer shareware manual, URL:,1998.
  10. H.-P. Schwefel, Numerische Optimierung von Computer-Modellen mittels der Evolutionsstrategie, Interdisciplinary Systems Research, vol. 26, Birkhäuser, Basel, 1977.Google Scholar
  11. W.M. Tolles, J.W. Nibler, J.R. McDonald and A.B. Harvey, A Review of the Theory and Application of Coherent Anti-Stokes Raman Spectroscopy (CARS), Applied Spectroscopy 31 (1977), 4, 253–271.CrossRefGoogle Scholar
  12. H.-M. Voigt, W. Ebeling, I. Rechenberg and H.-P. Schwefel (ed.), International Conference on Evolutionary Computation, Lecture Notes in Computer Science, vol. 1141, Springer, Berlin, September 1996.Google Scholar
  13. B. Wies, M. Dzubiella, X.X. Zhang, H. Minkenberg and D. Brüggemann, Temperature Fields in a Commercial Oil Spray Burner—Comparison of CARS and Thermocouple Measurements, Joint Meeting of the Soviet and Italian Sections of the Combustion Institute, 1990.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • U. Linnemann
    • 1
  • P. Roosen
    • 1
  • H.-J. Koß
    • 1
  1. 1.RWTH AachenLehrstuhl für Technische ThermodynamikAachenGermany

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