Quantitative correlation between stress variation and charge signals of loaded coal and its implication for dynamic fracturing of surrounding rock

To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways, this study systematically investigates the quantitative relationship between stress and charge signals during coal mass loading. By integrating innovative analytical approaches, introducing quantitative evaluation indices, and developing a charge–stress inversion model, and incorporating underground monitoring practices, significant progress has been achieved in elucidating the correlation between stress variations and charge signals throughout the entire coal mass fracturing process. First, in the field of stress–charge correlation analysis, empirical mode decomposition (EMD) was combined with wavelet coherence analysis for the first time, enabling the removal of slow-varying stress trends while retaining high-frequency fluctuations. This approach allowed for the quantitative characterization of the evolution of coherence between stress variations and charge fluctuations across multiple time scales. Second, coherence skewness and the proportion of high-coherence intervals were innovatively introduced to examine the influence of time scale selection on correlation results. On this basis, a criterion for determining the near-optimal observation scale of charge signals was proposed, providing a quantitative reference for time scale selection in similar signal analyses. Finally, by correlating charge signals with coal damage factors and stress states, a charge-based damage evolution equation was established to achieve effective stress inversion. Combined with in situ monitoring of stress and charge in roadway surrounding rock, this approach revealed the correlation characteristics of stress and charge intensity responses during the dynamic fracturing process. The results indicate, first, that charge signals are not significantly correlated with the absolute stress level of coal but are directly associated with stress variations following coal damage and failure, with the amplitude of charge fluctuations increasing alongside stress fluctuations. Second, coherence between stress and charge signals varies markedly across time scales, with excessively small or large scales leading to distortion, and the scale corresponding to the peak proportion of intervals with coherence > 0.8 was identified as the near-optimal observation scale. Third, charge signals can effectively characterize coal damage factors, and the established damage evolution equation can effectively invert stress variation trends. Fourth, in underground roadways, zones of dynamic fracturing in surrounding rock are commonly located in areas where stress concentration overlaps with regions of high charge intensity, further confirming the strong consistency between charge and stress variations. These findings improve the theoretical framework of charge signal responses in loaded coal and provide a scientific basis for precise “stress-charge” monitoring of dynamic disasters, offering practical potential for engineering applications.