Abstract
Aimed at investigating the differentiation of acoustic emission (AE) signals and fractal precursory characteristics between strong, weak, and no bursting liability coals under uniaxial compression, as well as improving the accuracy of rockburst monitoring and early warning by AE techniques, we experimentally studied the evolution law and differences of AE ring count rate, energy rate, and correlation dimension between different loaded bursting liability coals by the YAW4306 electric mechanical test system and CTA-1 AE monitor. Our experimental results indicated that the AE count and energy of coal samples with different bursting liabilities showed a similar evolution law of “sharp increase-calm-sharp increase” before their main rupture. The active points of AE signals emitted from coal with strong, weak, and no bursting liability appeared at about 85∼90%, 75∼78%, and 51∼55% of the peak stress, respectively. The stronger the bursting liability of coal, the shorter the duration of main rupture and postpeak failure stage, and the greater the AE energy rate in the main rupture. The AE counts of different coals had obvious fractal characteristics, and the AE correlation dimension values of strong and weak bursting liability coal samples presented the phenomenon of “fluctuating rise to a peak value-sharp drop-continuous decrease,” which can be used as a precursory information of coal failure.
Highlights
China is the world’s largest coal consumer and has experienced the most serious coal and rock dynamic disasters [1, 2], such as coal and gas outburst [3], rockburst [4], and roof fall [5]
Due to the differences in the degree of anisotropy, porosity, crack development, and failure process of coals with different bursting liabilities, the acoustic emission (AE) characteristics during the failure process are different. us, through laboratory loading compression tests of different bursting liability coals, this paper explores the differentiation of AE signals and fractal characteristics between coals with strong, weak, and no bursting liability and investigates the precursory information of coal in the failure process. e results provide a reference for further improving the forecasting accuracy of rockburst by AE techniques and have certain theoretical and practical significance for ensuring coal mine safety
As seen from the above figures, the AE signals emitted from loaded coal samples were significantly different between the five stages of the whole deformation and failure process
Summary
China is the world’s largest coal consumer and has experienced the most serious coal and rock dynamic disasters [1, 2], such as coal and gas outburst [3], rockburst [4], and roof fall [5]. Lotidis and Nomikos [24] studied the AE evolution law of hollow plate specimens of two calcitic marbles in the laboratory under uniaxial loading and found that the overall percentage of the signals attributed to tensile AE sources was in the order of 90%, while most of the located shear AE sources were nucleated after the sidewall’s rock failure He et al [25] discussed the failure process characteristics of limestone under true triaxial condition. Guo et al [45] discussed the AE fractal characteristics of coal samples with bursting liability under uniaxial loading and suggested the phenomenon that the AE fractal dimension reached a peak and a sudden drop, which could be used as a precursor to coal damage. Us, through laboratory loading compression tests of different bursting liability coals, this paper explores the differentiation of AE signals and fractal characteristics between coals with strong, weak, and no bursting liability and investigates the precursory information of coal in the failure process. Due to the differences in the degree of anisotropy, porosity, crack development, and failure process of coals with different bursting liabilities, the AE characteristics during the failure process are different. us, through laboratory loading compression tests of different bursting liability coals, this paper explores the differentiation of AE signals and fractal characteristics between coals with strong, weak, and no bursting liability and investigates the precursory information of coal in the failure process. e results provide a reference for further improving the forecasting accuracy of rockburst by AE techniques and have certain theoretical and practical significance for ensuring coal mine safety
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