Acoustic Inversion Reconstruction of Temperature Field for Hidden Fire Sources of Coal Spontaneous Combustion Considering Porous Propagation Effects

Coal spontaneous combustion fire is a major hazard threatening mine safety and production. Accurate identification of hidden fire sources is the key to preventing and controlling coal spontaneous combustion fires. Given that traditional detection methods are unable to accurately identify high-temperature zones, this study develops an acoustic-signal-based approach for reconstructing the temperature field associated with coal spontaneous combustion. By constructing a two-dimensional acoustic thermometry experimental system for temperature field measurement, multipath acoustic signals were collected in both the air medium and a loose coal medium, respectively. The variation characteristics of the acoustic spectrum, energy attenuation, and travel time were analyzed under different heat source temperatures, media, and sound source positions. The results show that the dominant frequencies of the received signals under different heat source temperatures are concentrated in the range of 1000–1300 Hz. An increase in temperature does not significantly alter the dominant frequency range, but it reduces the peak amplitude of the received signals. Compared with propagation in air, acoustic waves experience greater energy loss in loose coal. Their travel time is also generally longer, indicating that the pore structure alters the propagation path and influences the acoustic propagation process. To account for pore-structure-induced deviations between the actual acoustic propagation path and the geometric path, a path correction coefficient is introduced. Using the compensated correction model, the temperature fields under working conditions of 100 °C, 150 °C, and 200 °C were reconstructed, with peak temperatures of 91.507 °C, 140.554 °C, and 188.665 °C, respectively. The gap between the reconstructed results and those obtained in the air medium is significantly narrowed. This suggests the model effectively corrects path deviations due to pore structure and enhances acoustic reconstruction accuracy for non-uniform temperature fields in loose coal. These findings offer a methodological basis for acoustic temperature field reconstruction and hidden fire source detection in loose coal, with practical value for enhancing mine fire prevention efficiency.