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Detection of Signal of Fire Source for Coal Spontaneous Combustion Applied with Acoustic Wave

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Abstract

Coal spontaneous combustion can cause a series of problems in terms of wasted resources, casualties, and environmental pollution. Accurate detection of the fire source in loose coal is the key to preventing coal spontaneous combustion. Acoustic temperature measurement has significant advantages of strong stability, high accuracy, and wide measurement range, which can make up for the shortcomings of traditional fire source detection methods. Detecting the optimum source signal for loose coal temperature measurement is the basis and prerequisite for the realization of acoustic temperature measurement. Therefore, the anti-interference characteristics of three typical sound source signals were tested and analyzed through a self-designed sound wave propagation characteristic test system. The cross-correlations among maximum length sequence signal, pulse signal, and linear sweep signal were compared and analyzed. Compared to the other two signals, the main peak of the cross-correlation coefficient of the linear sweep signal was more prominent and its pseudo-peaks interfered less with its main peak. This signal had strong anti-interference ability, and it can be used as a basic acoustic source signal for temperature measurement of loose coal. To further screen out the optimal frequency band and length of the linear sweep signal, four bituminous coals were selected as the propagation medium. The main peak value and the difference between the main peak and the maximum pseudo-peak of the cross-correlation coefficient were proposed as the evaluation indicators. The optimum signal frequency bands of long-flame coal, non-caking coal, coking coal, and lean coal were 400–900, 400–900, 500–1200, and 400–900 Hz, and the optimum signal length of four coals was 0.1 s. The study results can provide theoretical support for the selection of acoustic temperature measurement signals for loose coal.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Nos. 52074215, 52204239, and 52174204), the Natural Science Basic Research Program of Shaanxi (Nos. 2022JQ–517, 2022JQ–446), and the Postdoctoral Research Foundation of China (No. 2022M722557).

Funding

National Natural Science Foundation of China, 52074215, Jun Deng, 52204239, Shuaijing Ren, 52174204,Yang Xiao, Natural Science Basic Research Program of Shaanxi Province, 2022JQ–517, Shuaijing Ren, 2022JQ–446, Teng Ma, Postdoctoral Research Foundation of China, 2022M722557, Shuaijing Ren.

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Authors and Affiliations

  1. School of Safety Science and Engineering, Xi’an University of Science and Technology, No. 58, Yanta Mid. Rd., Xi’an, 710054, Shaanxi, People’s Republic of China

    Shuaijing Ren, Yanni Zhang, Yang Xiao, Jun Deng, Teng Ma & Yutao Zhang

  2. School of Energy Engineering, Xi’an University of Science and Technology, No. 58, Yanta Mid. Rd., Xi’an, 710054, Shaanxi, People’s Republic of China

    Shuaijing Ren & Teng Ma

  3. Shaanxi Key Laboratory of Prevention and Control of Coal Fire, Xi’an University of Science and Technology, No. 58, Yanta Mid. Rd., Xi’an, 710054, Shaanxi, People’s Republic of China

    Yanni Zhang, Yang Xiao, Jun Deng & Yutao Zhang

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  1. Shuaijing Ren
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  3. Yang Xiao
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Correspondence to Shuaijing Ren or Yanni Zhang.

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Ren, S., Zhang, Y., Xiao, Y. et al. Detection of Signal of Fire Source for Coal Spontaneous Combustion Applied with Acoustic Wave. Nat Resour Res 32, 2243–2256 (2023). https://doi.org/10.1007/s11053-023-10225-0

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