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河南平顶山平煤矿区天然地震、爆破、塌陷时频特征分析
引用本文:高家乙,刘晓锋,闫睿.河南平顶山平煤矿区天然地震、爆破、塌陷时频特征分析[J].地震地磁观测与研究,2020,41(3):67-74.
作者姓名:高家乙  刘晓锋  闫睿
作者单位:中国郑州 450016 河南省地震局
基金项目:中国地震局监测、预报、科研三结合课题(项目编号:3JH-201901009)
摘    要:选取2019年3月—8月河南平顶山市宝丰县平煤矿区发生的ML 2.0—2.9天然地震、爆破、塌陷等9次震动事件,在区域地质构造背景和波形特征分析基础上,采用短时傅里叶变换(STFT)方法开展时频波谱分析,提取不同类型事件的时频特征。结果显示:①天然地震频率成分丰富,且高、低频分布均匀,P波在约3 Hz和8 Hz处存在2个峰值,S波存在多个峰值;②爆破事件的时频谱相对集中,以低频为主,P波频率峰值约5Hz,信号主频随时间变化,大致呈线性降低至1—2 Hz;③塌陷事件频率成分以4 Hz以下的低频为主,P波无明显峰值且频率成分单一,主频出现在2 Hz左右的面波。本文结果可为今后该矿区震动事件类型判断提供参考依据。

关 键 词:天然地震  爆破  塌陷  短时傅里叶变换  时频分析

Time-frequency analysis of seismic records generated by natural earthquakes,blasts, and collapses near Pingmei mine based on STFT
GAO Jiayi,LIU Xiaofeng,YAN Rui.Time-frequency analysis of seismic records generated by natural earthquakes,blasts, and collapses near Pingmei mine based on STFT[J].Seismological and Geomagnetic Observation and Research,2020,41(3):67-74.
Authors:GAO Jiayi  LIU Xiaofeng  YAN Rui
Institution:Henan Earthquake Agency, Zhengzhou 450016, China
Abstract:We selected nine seismic events with ML 2.0-2.9 generated by natural earthquakes, blasts, and collapses near Pingmei mine in Baofeng county from March to August 2019 to study time-frequency characteristics of their waveforms based on the STFT method. Frequency contents of natural earthquake records are abundant and distributed evenly. The P-phase seismic record has two peaks at about 3 Hz and 8 Hz, and S-phase seismic record has multiple peaks. The seismic energy of blasts is concentrated on the low-frequency part of spectrograms. The peak frequency of P-phase is about 5 Hz and decreases linearly to 1-2 Hz with time. Collapses mainly generate low-frequency seismic energy below 4 Hz. The P-phase record has no obvious peak frequency and its frequency content is simple. The result shows that the time-frequency characteristics of seismic records generated by different types of events are obviously different, which can be distinguished by the STFT time-frequency analysis method.
Keywords:natural earthquake  blast  collapse  STFT  time-frequency analysis
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