The influence of the internal structure of loaded composite coal-rock on the variation characteristics of electromagnetic radiation (EMR) signal

Abstract

In this study, authors analysed the distribution law of the loaded coal-rock internal current field, and then derived a theoretical model of the loaded composite coal-rock with fracture. Then, the influence of fracture state in coal-rock on the time-frequency characteristics of the EMR signal was studied, and the relationship between the EMR characteristics and the coal-rock states was summarized and verified by uniaxial experiments. The results showed that: the superposition of multiple micro-current sources in the loaded coal-rock leads to changes in the EMR, and the properties of the internal fracture of the coal-rock affect the distribution of the internal current field, which causes the external EMR intensity to exhibit a characteristic of “slow increase - slow increase - steady increase - slow increase - rapid decrease” with time. In addition, the proportion of internal charged fractures is highly correlated with the degree of damage, and there is a quadratic or linear fit between the internal charged fractures and the EMR intensity at each stress stage, with a fit above 93%. Meanwhile, the frequency-domain features contain more information than the time-domain's, and the more severe the damage to the coal-rock, the more complex the EMR spectrum measured from the outside will be. When the main frequency is around 5 kHz, the deformation of the coal-rock is mainly elastic, but when the main frequency is around 20 kHz, the damage is mainly plastic. On this basis, loaded coal-rock could be divided into six loading stages from I to VI according to EMR characteristics, and the EMR intensity, main frequency bandwidth, energy distribution characteristics and spectrum composition of each stage are different, which are related to the coal-rock's internal fracture state. Moreover, the experimental results are consistent with the theoretical and simulation results. These results can help improve the coupling theory between coal-rock internal structure and EMR, and have theoretical and reference value for the study of coal and rock dynamic disaster prevention methods based on multi-source information fusion.