Affiliation:
1. School of Mechanics and Engineering, Liaoning Technical University, Fuxin 123000, China
2. College of Mining, Liaoning Technical University, Fuxin 123000, China
3. School of Physics, Liaoning University, Shenyang 110036, China
Abstract
Monitoring and preventing coal–rock dynamic disasters are essential for ensuring sustainable and safe mining. Induced charge monitoring, as a geophysical method, enables sustainable monitoring of coal–rock deformation and failure. The induced charge signal contains crucial information regarding damage evolution, making it imperative and important to explore its temporal characteristics for effective monitoring and early warnings of dynamic disasters in deep mining. This paper conducted induced charge monitoring tests at different loading rates, investigating the multifractal characteristics of induced charge signals during the early and late stages of loading. It proposed the maximum generalized dimension D(q)max, multifractal spectrum width Δα, and height difference Δf as multifractal parameters for induced charge signals. Additionally, quantitative characterization of coal damage was performed, studying the variation patterns of signal multifractal characteristic parameters with coal damage evolution. This study revealed the induced charge signal of the coal body multifractal characteristics in the whole loading process. In the late loading stage, the double logarithmic curve demonstrated some nonlinearity compared to the previous period, indicating the higher non-uniformity of the induced charge time series. D(q)max and Δα in the late loading stage were higher than those in the early stage and increased with loading rates. As coal damage progressed, there were significant jumps of D(q)max in both the early and late stages of damage, with larger jumps indicating richer fracture events in the coal. The width Δα showed an overall trend of increase–decrease–increase with coal damage evolution, while the height difference Δf fluctuated around zero in the early stage of damage development but increased significantly during severe damage and destruction. By studying the multifractal characteristics of induced charge signals, this study provides insights for the early identification of coal–rock dynamic disasters.
Funder
National Natural Science Foundation of China
Hebei Key Laboratory of Mine Intelligent Unmanned Mining Technology
Fundamental Research Project of the Educational Department of Liaoning Province
Reference32 articles.
1. Rock dynamics in deep mining;He;Int. J. Min. Sci. Technol.,2023
2. Safe mining operations through technological advancement;Onifade;Process Saf. Environ. Prot.,2023
3. Research review of the state key research development program of China: Deep rock mechanics and mining theory;Xie;J. China Coal Soc.,2019
4. Damage Constitutive Model of Gas-bearing Coal using Industrial CT Scanning Technology;Wu;J. Nat. Gas Sci. Eng.,2022
5. Monitoring and Pre-warning of Rockburst Hazard with Technology of Stress Field and Wave Field in Underground Coalmines;Dou;Chin. J. Rock Mech. Eng.,2017
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