Infrared Technology, Volume. 46, Issue 3, 354(2024)

Research on Infrared Effective Detection Distance for Predicting Spontaneous Combustion of Goaf Residual Coal Based on Non-contact Mode

Xiaoqiang WANG1, Wansheng MI2, and Yongchen YANG3,4、*
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    The spontaneous combustion of residual coal in a goaf is a major cause of underground fire accidents in coal mines. Owing to the actual situation of underground goafs, existing detection methods cannot directly determine the true situation of residual coal thermal storage and spontaneous combustion. This study utilized the non-contact temperature measurement characteristics of the infrared thermal imager, and through the analysis of temperature measurement principles, experimental system design, and construction methods, conducts an experiment to measure the effective detection distance of the FOTRIC348 infrared thermal imager close to the real environment of the underground goaf, and verifies it in underground engineering. The results show that the effective detection distances of the FOTRIC348 in the regional, line, and point temperature measurement modes were 8 m to 12 m, 10 m to 13 m, and 9 m to 13 m, respectively. The effective detection distance of FOTRIC348 during underground testing was 10 m to 12 m. Based on the intersection of the above detection distances, the effective detection distance of the FOTRIC348 infrared thermal imager for determining the thermal storage and spontaneous combustion stage of residual coal in the goaf of the two parallel grooves of the working face is 10 m to 12 m. Determining this value can provide a targeted decisionmaking basis for implementing prevention and control measures for spontaneous coal combustion in the goaf.

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    WANG Xiaoqiang, MI Wansheng, YANG Yongchen. Research on Infrared Effective Detection Distance for Predicting Spontaneous Combustion of Goaf Residual Coal Based on Non-contact Mode[J]. Infrared Technology, 2024, 46(3): 354

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    Paper Information

    Category:

    Received: Jul. 28, 2023

    Accepted: --

    Published Online: Sep. 2, 2024

    The Author Email: Yongchen YANG (w1108hh@163.com)

    DOI:

    CSTR:32186.14.

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