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Characterizing rockbursts and analysis on frequency-spectrum evolutionary law of rockburst precursor based on microseismic monitoring

机译:基于微震监测的岩爆前体频谱进化法的特征及分析

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The access tunnel in the main powerhouse of the Shuangjiangkou hydropower station in China has complex geological conditions with high in-situ stress. Rockbursts pose serious threats to the safety of personnel and equipment in the tunnel. Three-dimensional microseismic (MS) monitoring technology was used to explore MS activities inside the tunnel surrounding rock. In consideration of various kinds of signals, the Fast Fourier Transform (FFT) method was employed to obtain the amplitude-frequency spectra of signal waveforms, and then, some waveform characteristics (amplitude, duration, dominant frequency distribution range, peak frequency, main frequency value, etc.) were analyzed to recognize MS signals. It provided a guarantee for further analysis of signals, and also provided significant guidance for MS signal recognition in other tunnels. Based on MS activity frequency and released energy time-series curves, the rockburst sequence type in the tunnel can be determined as foreshock-mainshock-aftershock. Studying spatiotemporal distribution characteristics of microcracks inside the surrounding rock, dominant active areas inside the surrounding rock of the tunnel have been delimited. In addition, a more efficient signal analysis technique (wavelet packet transform) was used to frequency-decompose complex MS waveforms and the dominant information of signals was retained; furthermore, a time-frequency model was first established to analyze the activity characteristics inside the surrounding rock; by using the model we can more intuitively analyze and accurately judge rockburst precursor information. The results indicated that a downward shift phenomenon of frequency band energy distribution can be used as an early warning indicator of rockbursts.
机译:中国双江口水电站主电站的通道隧道具有复杂的地质条件,良好地应力。摇滚笨蛋对隧道中的人员和设备的安全构成了严重的威胁。三维微震(MS)监测技术用于探索隧道周围岩石内的MS活动。考虑到各种信号,采用快速傅里叶变换(FFT)方法来获得信号波形的幅度频谱,然后,一些波形特性(幅度,持续时间,主频分布范围,峰值频率,主频率分析值等)以识别MS信号。它为进一步分析了信号提供了一种保证,并且还提供了在其他隧道中的MS信号识别的显着指导。基于MS活动频率和释放的能量时间曲线,隧道中的岩爆序列类型可以被确定为ForeShock-Mainshock-eftershock。研究周围岩石内微裂纹的时空分布特性,隧道周围岩石内的主干区域已经界定。另外,更有效的信号分析技术(小波分组变换)用于频率分解复杂的MS波形,并保留信号的主导信息;此外,首先建立时频模型,以分析周围岩石内的活动特性;通过使用该模型,我们可以更直观地分析和准确地判断摇滚乐前体信息。结果表明,频带能量分布的向下移位现象可以用作摇滚乐的预警指标。

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