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用能量累积法检测地震波雷达信号

Using the method of accumulating energy for detecting seismic wave radar signal

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【作者】 刘明辉周银兴彭朝勇陈阳李江王洪体

【Author】 LIU Ming-Hui;ZHOU Yin-Xing;PENG Chao-Yong;CHEN Yang;LI Jiang;WANG Hong-Ti;Key Laboratory of Earthquake Prediction,China Earthquake Administration;Institute of Earthquake Science,China Earthquake Administration;Institute of Geophysics,China Earthquake Administration;

【机构】 中国地震局地震预测重点实验室中国地震局地震预测研究所中国地震局地球物理研究所

【摘要】 将具有高度重复性的地震波雷达长时间向地壳内发射线性调频信号,经过地下介质的传播后到达地面,用地震仪器在监测点和检测点记录下来,通过分析数据来了解地壳速度结构及波速变化.线性调频信号是一种非平稳信号,它的频率随时间线性变化,有很好的能量聚集性,非常适合做时间-频率分析.本文用短时傅里叶变换对监测点的信号进行时间-频率分析,以检验地震波雷达发射信号的时间和频率是否和控制系统一致.通过WignerVille分布将地震波雷达发射的信号能量聚集在线性调频直线上,再用Hough变换累积聚集的能量形成波峰,按照线性调频直线的倾角提取波峰所在行,计算到时后构成地震波走时曲线图.用靠近本次实验地点的H-21剖面得到的地壳速度结构正演该测线的Pg、Sg、PmP和SmS的折合走时曲线,并与用能量累积法提取出的地震波走时曲线进行对比,分析结果表明:地震波雷达发射线性调频信号的时间和频率都符合控制要求,重复性高达99.9%以上,可以清晰地分辨出Pg、Sg震相,并且PmP和SmS震相可辨.

【Abstract】 How to identify seismic wave velocity anomalies and to study their characteristics has practical significances for earthquake study and prediction.Almost all disastrous earthquakes in China′s mainland have occurred in the Earth′s crust within depth of 5~25km.Therefore,dynamic monitoring physical parameters of the Earth′s crust is an effective approach to predicting earthquakes.Seismic Wave Radar(SWR)is a type of mechanical and electrical devices.It continuously excites Linear Frequency Modulation(LFM)signals into the Earth′s crust,and these signals are recorded by high sensitivity seismographs at the deployment sites.How to retrieve impulsive seismic waveforms from the recorded data which include signals and differentkinds of noises is very important for calculating accurate travel times and temporal velocity variation.In this work,we propose a new method for processing the SWR data,which is based on accumulating energy in time-frequency domain.LFM is a non-stationary signal and its frequencies vary linearly as a function of time and have a good energy concentration,so it is very suitable for time-frequency analysis.We use Short-Time Fourier Transform(STFT)to analyze the data recorded by the monitoring stations,and acquire the time-frequency distribution,in order to validate whether the excitation time and frequencies are consistent with those set by the control system of SWR.Then,two methods are introduced for the waveform retrieval from the SWR data.One is the Wigner-Ville Distribution(WVD)algorithm with the best time-frequency concentration capability for the LFM signals,and the other one is the Wigner-Hough Transform(WHT)which is helpful to suppress the cross-time interference in the signal detection and parameter estimation for the multi-component LFM signals.By aggregating energy of the excited signals of the SWR on the LFM line with WVD method and accumulating the concentration energy to a crest by WHT,we can extract the peak row according to the inclination angle of the LFM line and compose the seismic wave travel-time curve after calculating the travel time.Firstly,in order to quantify the repeatability of the SWR,we calculated cross-correlation coefficients of all waveform pairs retrieved from different time windows.Within the total 126hours′SWR data,cross-correlations coefficients of 123hours′are bigger than 0.999.The high correlations between the waveforms indicate the excellent repeatability of the SWR.In addition,the results obtained from STFT methods show that the excitation time and frequencies of the LFM signals met the control requirements and the repeatability is more than 99.9%.Finally,the crustal velocity structure obtained from the H-21 section near the location of this experiment was used to calculate the reduced travel-time curves of Pg,Sg,PmP and SmS of the detecting line,which were compared with those retrieved by our method.The results demonstrate that the proposed method is an effective way for retrieving waveform,identifying seismic phase and measuring travel time.By using this method,we can clearly identify Pg and Sg,and high frequency seismic phases such as PmP and SmS with strong amplitude in some epicenter distances can be discernable.In all,the SWR with high repeatability can be easily applied to monitoring temporal changes and imaging the spatial variations of the subsurface structure.The proposed method provides a feasible way to process the SWR data and advance its application in monitoring the crustal processes.

【基金】 国家科技支撑计划专题(2012BAF14B12-04);国家自然科学基金项目(41404048);中国地震局地震预测研究所基本科研业务专项(2010IES0201);中国地震局地球物理研究所基本科研业务专项(DQJB14B05)联合资助
  • 【文献出处】 地球物理学报 ,Chinese Journal of Geophysics , 编辑部邮箱 ,2015年04期
  • 【分类号】P631.4
  • 【被引频次】4
  • 【下载频次】122
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