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Experimental investigations on temperature distributions of flame sections in a bench-scale opposed multi-burner gasifier

Author

Listed:
  • Yan, Zhuoyong
  • Liang, Qinfeng
  • Guo, Qinghua
  • Yu, Guangsuo
  • Yu, Zunhong

Abstract

Based on a flame image processing technique, the temperature distributions of flame sections in a bench-scale opposed multi-burner (OMB) gasifier is visualized. With the assumption of the gray radiation, a charge-coupled device camera installed on the top of the gasifier is used to capture the approximately monochromatic radiant images under the visible wavelengths. To reduce the errors, the camera is calibrated by a blackbody cavity. By using the two-color method, the radiant intensity captured by the camera is calculated from the pair of red/green with reference to the calibration data. Based on the assumption of rotational symmetry, the temperature distributions of flame sections are reconstructed by the Filtered back-projection method. The results show that the temperature distributions of flame sections are consistent with the flame structure. The flame temperature distribution at the burner plane ranges from 1700 to 2100 °C. The section is farther from the burner plane, the temperature is lower. The relative errors between the calculated temperatures and the measured temperatures by a B-type thermocouple are no greater than ±6.4%. The research results establish the foundation for understanding the flame internal structure and temperature distribution in the OMB gasifier.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:86:y:2009:i:7-8:p:1359-1364
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    Citations

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    Cited by:

    1. 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.
    2. Gong, Yan & Zhang, Qing & Zhu, Huiwen & Guo, Qinghua & Yu, Guangsuo, 2017. "Refractory failure in entrained-flow gasifier: Vision-based macrostructure investigation in a bench-scale OMB gasifier," Applied Energy, Elsevier, vol. 205(C), pages 1091-1099.
    3. 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.
    4. Gong, Yan & Zhang, Qing & Guo, Qinghua & Xue, Zhicun & Wang, Fuchen & Yu, Guangsuo, 2017. "Vision-based investigation on the ash/slag particle deposition characteristics in an impinging entrained-flow gasifier," Applied Energy, Elsevier, vol. 206(C), pages 1184-1193.
    5. 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.

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