负压环境下结构煤破坏的声发射频谱特征

Aohan Zhao, Yankun Ma, Deren Chen, Dengke Wang, Meng Wang
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引用次数: 0

摘要

利用结构煤样进行了低压环境下的单轴压缩实验。通过 FFT 变换和小波包分解获得了煤块在低压环境下加载失效的频域响应特征。结果表明随着煤的加载应力增大,AE频谱变得更加丰富,整个AE频谱呈左移趋势。当瓦斯压力增大时,声发射信号由低频高能变为高频低能,频带逐渐叙述,频谱由复杂的多峰形变为单峰形。随着应力的增加,0-4.38 kHz 频段的能量比例逐渐增加,而其他频段的能量比例逐渐减少。2.92-4.38 kHz 和 4.38-5.84 kHz 两个频段的能量对应力变化的响应最为明显。当压力发生变化时,2.92-4.38 kHz、4.38-5.84 kHz 和 7.3-8.76 kHz 三个频段的能量随压力变化呈现明显的响应趋势,且后两者的响应趋势(增加)与前者正好相反(减少)。这一现象表明,2.92-4.38 kHz 和 4.38-5.84 kHz 是煤断裂过程的特征频段。这一研究结果为煤与瓦斯突出危险的监测和预警提供了重要的基础数据支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Acoustic emission spectrum characteristics of structural coal destruction in negative pressure environment
The uniaxial compression experiments under a low-pressure environment were performed by using structural coal samples. The frequency domain response characteristics of coal mass failure under loading in a low-pressure environment were acquired by FFT transformation and wavelet packet decomposition. The results show: As the loading stress of coal increases, the AE spectrum becomes more abundant, and the whole AE spectrum shows a left-shift trend. When the gas pressure increases, the acoustic emission signals change from low-frequency high-energy to high-frequency low-energy, the frequency band gradually narrates, and the spectrum changes from complex multi-peak shape to single-peak shape. As stress increases, the proportion of energy in the band 0-4.38 kHz gradually increases, while that in other bands gradually decreases. The energy response to stress changes in the two frequency bands of 2.92-4.38 kHz and 4.38-5.84 kHz is the most obvious. When the pressure changes, the energy in three frequency bands of 2.92-4.38 kHz, 4.38-5.84 kHz, and 7.3-8.76 kHz present an evident response trend with the pressure change, and the response trend (increase) of the latter two is exactly opposite (decrease) to that of the former. This phenomenon indicates that 2.92-4.38 kHz and 4.38-5.84 kHz are the characteristic frequency bands of the coal fracture process. The findings of this research offer crucial foundational data to support the monitoring and early warning of coal and gas outburst hazards.
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