Improving Mining Sustainability and Safety by Monitoring Precursors of Catastrophic Failures in Loaded Granite: An Experimental Study of Acoustic Emission and Electromagnetic Radiation

Dongming Wang, Yankun Ma (), Xiaofei Liu (), Dexing Li, Quanlin Liu, Hengze Yang and Xuelong Li
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Dongming Wang: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
Yankun Ma: Key Laboratory of Safety and High–Efficiency Coal Mining, Anhui University of Science and Technology, Huainan 232001, China
Xiaofei Liu: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
Dexing Li: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
Quanlin Liu: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
Hengze Yang: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
Xuelong Li: College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao 266590, China

Sustainability, 2024, vol. 16, issue 3, 1-16

Abstract: Effective monitoring and early warning methods are crucial for enhancing safety and sustainability in deep coal resource extraction, particularly in mitigating rock burst disasters triggered by abrupt rock failure under high–ground–stress conditions. This paper presents the results of experimental investigations that involved conventional uniaxial direct and graded mechanical tests on granite that concurrently collected acoustic emission (AE) and electromagnetic radiation (EMR) signals. This study focused on the temporal evolution patterns of characteristic parameters in AE and EMR signals during granite deformation and fracture processes. To deconstruct and understand these temporal evolution characteristics, multifractal and critical slowing–down theories are introduced. The research findings reveal significant correlations between the evolution of AE and EMR characteristic parameters and the stages of rock deformation and fracture. Notably, dynamic changes in multifractal parameters (Δα and Δf) quantitatively reflected the deformation and fracture processes, with abrupt increases in Δα and sudden decreases in Δf closely associated with large–scale rock fractures. The temporal continuity of critical slowing–down parameters (variance and autocorrelation coefficient) demonstrated increased sensitivity as rock destruction approaches, with the variance emerging as a crucial indicator for large–scale fractures. This study observed a sudden increase in the variance of AE and EMR signals when the stress level reached 80–90% of the peak stress. Joint monitoring through diverse methods and multiple indicators enhanced the effectiveness of rock burst disaster warnings, contributing to the safety and sustainability of coal resource extraction. Further refinement and exploration of these indicators offer promising avenues for advancing rock failure monitoring and early warning capabilities in coal mines.

Keywords: AE; EMR; multifractal; critical slowing–down (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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