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Discrimination of different blasting and mine microseismic waveforms using FFT, SPWVD and multifractal method
Environmental Earth Sciences ( IF 2.8 ) Pub Date : 2021-01-08 , DOI: 10.1007/s12665-020-09330-7
Baolin Li , Enyuan Wang , Zhonghui Li , Yue Niu , Nan Li , Xuelong Li

To distinguish various blasting and mine microseismic (MS) waveforms, the time–frequency characteristics and non-linear characteristics of mine MS waveforms caused by mining activities and different blasting waveforms (loosening blasting, pre-splitting blasting and deep-hole blasting) are analyzed using fast Fourier transform (FFT), smoothing pseudo-Winger-Ville distribution (SPWVD) and multifractal method. The results indicate that (1) Time–frequency spectrum of SPWVD can show the dynamic change of energy with time and instantaneous frequency. For mine MS waveforms, the energy and instantaneous frequency show a gradual attenuation trend with time. The larger the fracture strength of coal and rock caused by blasting, the higher the energy distributed in low frequency zone. (2) The dominant frequency obtained by FFT can divide the four types of waveforms into two types. The dominant frequency of loose blasting and deep-hole blasting waveforms are greater than 135 Hz, while that for pre-split blasting and mining MS waveforms are less than 135 Hz. (3) The loose blasting and deep-hole blasting waveforms can be distinguished by duration. The duration of loose blasting waveforms are less than 220 ms, while that for deep-hole blasting waveforms are greater than 220 ms. (4) Multifractal parameters (Δα and Δf(α)) can reflect the difference of local fluctuation intensities and heterogeneities of different waveforms and be affected by dominant frequency, duration and post-peak attenuation. The Δα and Δf(α) of pre-split blasting waveforms are less than 0.78 and − 0.2, respectively, while that for mine MS waveforms are opposite.



中文翻译:

使用FFT,SPWVD和多重分形方法区分爆破和矿山微震波形

为了区分各种爆破和矿山微震(MS)波形,分析了由采矿活动和不同爆破波形(松动爆破,预裂爆破和深孔爆破)引起的矿山MS波形的时频特性和非线性特性。使用快速傅立叶变换(FFT),平滑伪Winger-Ville分布(SPWVD)和多重分形方法。结果表明:(1)SPWVD的时频谱可以显示能量随时间和瞬时频率的动态变化。对于矿山MS波形,能量和瞬时频率显示出随时间逐渐衰减的趋势。爆破引起的煤和岩石的断裂强度越大,低频区域的能量分布就越高。(2)通过FFT获得的主频可以将四种波形分为两种。疏密爆破和深孔爆破波形的主要频率大于135 Hz,而预裂爆破和采矿的MS波形的主要频率小于135 Hz。(3)疏松爆破和深孔爆破波形可以通过持续时间来区分。疏松爆破波形的持续时间小于220 ms,而深孔爆破波形的持续时间大于220 ms。(4)分形参数(Δ 疏松爆破波形的持续时间小于220 ms,而深孔爆破波形的持续时间大于220 ms。(4)分形参数(Δ 疏松爆破波形的持续时间小于220 ms,而深孔爆破波形的持续时间大于220 ms。(4)分形参数(ΔαΔfα))可以反映不同波形的局部波动强度和异质性的差异,并且受主导频率,持续时间和峰后衰减的影响。的Δ α和Δ ˚Fα预裂爆破波形)小于0.78和- 0.2,分别,而对雷MS波形是相反的。

更新日期:2021-01-08
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