太原基准地震台和东山地震台地脉动信号分析研究
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摘要
应用太原基准地震台和东山地震台2007年至今的数字化资料进行研究,得到太原台、东山台地脉动噪声RMS值和功率谱密度,及其相应的卓越周期,找出两个台主要干扰源的频带范围。另外,采用Matlab提供的FFT算法对整点地震记录进行频谱计算,对2010年6月5日发生的太原市阳曲Ms4.6地震前两个台记录的数字地脉动信号进行实时连续跟踪对比观测和试验,捕捉临震特殊频率波动现象,作为一种可能的"地震前兆"作探索性的研究。所得结果对去除数字地脉动信号背景干扰及分析预报工作具有借鉴作用。
Base on the digital data recorded by Taiyuan and Dongshan stations since 2007,the RMS value(m/s),power spectral density and the corresponding period(predominate period) of background noise of Taiyuan and Dongshan stations are obtained and the frequency band range of the main noise sources of the two stations is found.In addition,the real-time and continuous contrast observation and test of the digital background signals recorded by Taiyuan and Dongshan stations before 5 June 2010 Yangqu M4.6 earthquake are carried out based on the spectrum calculation results of the hour seismic records using the FFT algorithm from Matlab.The purpose of this work is to capture impending-earthquake wave phenomenon with special frequency and to see if this phenomenon as one possible earthquake precursor.The result may provide reference for getting rid of background noise and for earthquake prediction work.
Base on the digital data recorded by Taiyuan and Dongshan stations since 2007,the RMS value(m/s),power spectral density and the corresponding period(predominate period) of background noise of Taiyuan and Dongshan stations are obtained and the frequency band range of the main noise sources of the two stations is found.In addition,the real-time and continuous contrast observation and test of the digital background signals recorded by Taiyuan and Dongshan stations before 5 June 2010 Yangqu M4.6 earthquake are carried out based on the spectrum calculation results of the hour seismic records using the FFT algorithm from Matlab.The purpose of this work is to capture impending-earthquake wave phenomenon with special frequency and to see if this phenomenon as one possible earthquake precursor.The result may provide reference for getting rid of background noise and for earthquake prediction work.
引文
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