Study on the Propagation Response Characteristics of Acoustic Detection Signals for Coal Spontaneous Combustion in Goaf

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Abstract
The mine goaf is a caved space formed by the random accumulation of residual coal, broken rock fragments, and gangue, and is prone to disasters such as spontaneous combustion of residual coal and gas explosions. The accumulation state of loose media in the goaf affects the propagation variation in acoustic signals. Achieving acoustic detection in the goaf critically depends on the choice of the sound source signal. To study the acoustic behavior of typical unconsolidated goaf materials, coal, limestone, and coal gangue were taken as the test media. Industrial CT scanning and sound absorption tests, together with 3D reconstruction, were used to study the pore features and sound absorption behavior of various loose media. The results indicate that the pore structure of loose media exhibits pronounced multiscale characteristics. As the particle size of loose media increases, the pore structure exhibits a trend of increasing pore size accompanied by a decrease in the number of pores. Based on the analysis of mechanical parameters of the loose media, the elastic moduli of the three media are found to be on the order of 103 to 104 MPa, and the Poisson’s ratios are generally distributed in the range of 0.21–0.36. This indicates that all three media are rigid porous media. Sound absorption tests show that the maximum absorption coefficient of the three loose media decreases with particle size but increases with packing thickness. In rigid porous media, the acoustic absorption behavior of loose materials is governed by their pore structure variations. These findings lay a theoretical foundation for the acoustic identification of spontaneous coal combustion in goafs and present new technical avenues for mine safety and hazard management.
Funding Information
  • Key Research and Development Program of Shaanxi Province (2025GH-YBXM-054)
  • National Natural Science Foundation of China (52204239)
  • Young Elite Scientists Sponsorship Program by CAST (2023QNRC001)

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