Korean Journal of Chemical Engineering

, Volume 26, Issue 2, pp 489–495 | Cite as

Application of near infrared diffuse reflectance spectroscopy for on-line measurement of coal properties

  • Dong Won Kim
  • Jong Min LeeEmail author
  • Jae Sung Kim
Materials (Organic, Inorganic, Electronic, Thin Films)


The applicability of the Multi-wavelength Near-infrared sensor to analyze coal properties such as proximate analysis (moisture, ash, volatile matter, fixed carbon), ultimate analysis (carbon, hydrogen, nitrogen, oxygen, sulfur) and heating value is discussed. The most useful wavelengths (1,680, 1,942, 2,100, 2,180, 2,300 nm) for determining coal properties concentration were chosen by analyzing the NIR spectrum according to coal properties. Absorbances at the characteristic wavelength obtained from 128 mixed coal samples, which are using at a conventional thermal power plant, were correlated to the coal properties by using multiple regression analysis. The accuracy of coal analysis was examined by calculating the RMSEC (%), RMSEP (%), comparing the error with ASTM/ISO tolerance and performing paired Student’s T-test. The result of on-line coal analysis for all moisture, volatile matter, fixed carbon, carbon, hydrogen and heating value is not different from that of ASTM/ISO traditional methods at 90% confidence level. The technology appears suitable for the determination of several coal prorperties. If calibrated periodically, this on-line analysis of coal properties is helpful to efficiently operate a coal fired power plant.

Key words

NIR Absorbance Coal Properties Real-time Analysis 


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  1. 1.
    M. P. Fuller and P. R. Griffiths, Anal. Chem., 50(13), 1906 (1978).CrossRefGoogle Scholar
  2. 2.
    M. P. Fuller, I. M. Hamadeh, P. R. Griffiths and D. E. Lowenhaupt, Fuel, 61(6), 529 (1982).CrossRefGoogle Scholar
  3. 3.
    P.M. Fredericks, R. Kobayashi and P.R. Osborn, Fuel, 66(11), 1603 (1987).CrossRefGoogle Scholar
  4. 4.
    S. V. Pisupati and A. W. Scaroni, Fuel, 72(3), 531 (1993).CrossRefGoogle Scholar
  5. 5.
    A. Koch, A. Krzton, G. Finqueneisel, O. Heintz, J.V. Weber and T. Zimmy, Fuel, 77(6), 563 (1998).CrossRefGoogle Scholar
  6. 6.
    H. Machnikowska, A. Krzton and J. Machnikowski, Fuel, 81(2), 245 (2002).CrossRefGoogle Scholar
  7. 7.
    M. Kaihara, T. Takahashi, T. Akazawa, T. Sato and S. Takahashi, Spectrosc. Lett., 35(3), 369 (2002).CrossRefGoogle Scholar
  8. 8.
    J. M. Andres and M. T. Bona, Anal. Chim. Acta, 535(1), 123 (2005).CrossRefGoogle Scholar
  9. 9.
    J. M. Andres and M. T. Bona, Talanta, 70(4), 711 (2006).CrossRefGoogle Scholar
  10. 10.
    D.W. Kim, J. M. Lee, J. S. Kim and H. J. Kim, Korean Chem. Eng. Res., 45(6), 596 (2007).CrossRefGoogle Scholar
  11. 11.
    H. I. Jung and H. J. Kim, Analytical Science & Technology, 13(1), 1 (2000).Google Scholar
  12. 12.
    K. R. Beebe, R. J. Pell and M. B. Seasholtz, Chemometrics: A practical guide, John Wiley & Sons, Inc., 255–256 (1998).Google Scholar
  13. 13.
    D. C. Harris, Quantitative chemical analysis, Freeman, Inc., 62–63 (2007).Google Scholar

Copyright information

© Springer 2009

Authors and Affiliations

  1. 1.Power Generation LaboratoryKorea Electric Power Research InstituteDaejeonKorea

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