The automation of top coal caving is crucial for advancing unmanned coal mining technologies. During the top coal caving process, a coal-gangue mixture—comprising coal, gangue, and air—forms at the tail beam of hydraulic supports. This mixture exhibits diverse electromagnetic parameters, volumes, and shapes. This study investigates the propagation characteristics of electromagnetic waves within a coal-gangue mixture model and examines how varying operational conditions affect wave propagation. A novel three-dimensional reconstruction method based on multi-view imaging is introduced to accurately capture the geometric characteristics of coal and gangue blocks. Furthermore, a firefly optimization algorithm is enhanced to develop a random medium model that effectively simulates the spatial distribution and electromagnetic properties of coal-gangue mixtures. Results from CST simulations reveal significant insights into the propagation behavior of electromagnetic waves under differing dielectric constants, conductivities, and moisture contents. These findings underscore the potential for improving coal-gangue identification techniques in automated mining operations.
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