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Coal flame characterization by means of digital image processing in a semi-industrial scale PF swirl burner

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  • González-Cencerrado, A.
  • Peña, B.
  • Gil, A.

Abstract

The potential of a new procedure of image processing for the characterization of a given combustion state through flame visualization is here presented and discussed. Experimental tests were carried out in a swirl-stabilized, semi-industrial scale burner of 500kWth. Using an advanced vision based system, flame images have been recorded and subsequently processed, obtaining both luminous and spectral parameters from the grey values registered by each individual pixel. The acquisition system is based on a CCD (charge-coupled device) camera of high-speed frame rate. The innovative nature of the analysis lies in the 2D distribution of statistical and oscillatory parameters which can be interpreted as a “fingerprint” of the flame condition. By this method, flame spatial characterization was achieved allowing the identification of areas with different luminous and oscillating patterns. Their evolution regarding primary air-to-fuel ratio was also studied. First results suggest changes on flame symmetry and oscillation regimen. Additionally, quantitative flame analysis through global values of selected parameters and regression studies were conducted in order to analyse their usefulness for the development of monitoring and control algorithms in the combustion facility.

Suggested Citation

  • González-Cencerrado, A. & Peña, B. & Gil, A., 2012. "Coal flame characterization by means of digital image processing in a semi-industrial scale PF swirl burner," Applied Energy, Elsevier, vol. 94(C), pages 375-384.
    • Handle: RePEc:eee:appene:v:94:y:2012:i:c:p:375-384
    DOI: 10.1016/j.apenergy.2012.01.059
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    References listed on IDEAS

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    1. Yan, Zhuoyong & Liang, Qinfeng & Guo, Qinghua & Yu, Guangsuo & Yu, Zunhong, 2009. "Experimental investigations on temperature distributions of flame sections in a bench-scale opposed multi-burner gasifier," Applied Energy, Elsevier, vol. 86(7-8), pages 1359-1364, July.
    2. Chen, Junghui & Hsu, Tong-Yang & Chen, Chih-Chien & Cheng, Yi-Cheng, 2010. "Monitoring combustion systems using HMM probabilistic reasoning in dynamic flame images," Applied Energy, Elsevier, vol. 87(7), pages 2169-2179, July.
    3. Hwang, Cheol-Hong & Lee, Seungro & Kim, Jong-Hyun & Lee, Chang-Eon, 2009. "An experimental study on flame stability and pollutant emission in a cyclone jet hybrid combustor," Applied Energy, Elsevier, vol. 86(7-8), pages 1154-1161, July.
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    Cited by:

    1. Chen, Junghui & Chan, Lester Lik Teck & Cheng, Yi-Cheng, 2013. "Gaussian process regression based optimal design of combustion systems using flame images," Applied Energy, Elsevier, vol. 111(C), pages 153-160.
    2. Zhongya Xi & Zhongguang Fu & Syed Waqas Sabir & Xiaotian Hu & Yibo Jiang & Tao Zhang, 2018. "Experimental Analysis on Flame Flickering of a Swirl Partially Premixed Combustion," Energies, MDPI, vol. 11(9), pages 1-14, September.
    3. Peña, B. & Pallarés, J. & Bartolomé, C. & Herce, C., 2018. "Experimental study on the effects of co-firing coal mine waste residues with coal in PF swirl burners," Energy, Elsevier, vol. 157(C), pages 45-53.
    4. Zhou, Dongdong & Cheng, Shusen, 2019. "Measurement study of the PCI process on the temperature distribution in raceway zone of blast furnace by using digital imaging techniques," Energy, Elsevier, vol. 174(C), pages 814-822.
    5. Ögren, Yngve & Tóth, Pál & Garami, Attila & Sepman, Alexey & Wiinikka, Henrik, 2018. "Development of a vision-based soft sensor for estimating equivalence ratio and major species concentration in entrained flow biomass gasification reactors," Applied Energy, Elsevier, vol. 226(C), pages 450-460.
    6. Pallarés, Javier & Herce, Carlos & Bartolomé, Carmen & Peña, Begoña, 2017. "Investigation on co-firing of coal mine waste residues in pulverized coal combustion systems," Energy, Elsevier, vol. 140(P1), pages 58-68.

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