小波分析法在海拉尔地震台前兆数据处理中的应用研究

应用小波变换法可对不同频率成分进行分解的特性,选取db4小波基函数,尺度为1~8阶,对海拉尔地震台前兆资料进行分析研究。结果表明,应用小波变换方法可较容易地识别和剔除气压、场地环境干扰等影响海拉尔地震台伸缩仪观测资料精度的诸多因素,气压和场地环境干扰在小波细节分解d 3~d 6部分异常显著;小波变换法对同震效应的识别、提取和去除具有良好效果,远震在小波细节分解d 3~d 5部分异常显著,近震在小波细节分解d 1~d 3、d 6~d 8部分明显;爆破信号在小波分解d 1~d 8部分中均清晰可见,异常的宽度和幅度变化不大。因此,应用小波分解法能有效识别无法判断的干扰源。

Research on the Application of Wavelet Analysis Method in Precursor Data Processing at Hailaer Seismic Station

According to the characteristics that different frequency components can be decomposed by wavelet transform,db4 wavelet basis function with scale of 1-8 order is selected to analyze the precursor data of Hailaer seismic station.The results show that the application of wavelet transform method can easily identify and eliminate many factors that affect the accuracy of the extensometer observation data at Hailaer seismic station,such as air pressure and site environment interference.The disturbance of air pressure and site environment is significant in d 3-d 6 part of wavelet detail decomposition.Wavelet transform has a good effect on the identification,extraction and removal of coseismic effect.The remote earthquake is remarkable in the d 3-d 5 part of wavelet detail decomposition,and the near earthquake is obvious in the d 1-d 3 and d 6-d 8 parts of wavelet detail decomposition.The blasting signal is clearly visible in the d 1-d 8 part of wavelet decomposition,and the width and amplitude of the anomaly change little.Therefore,the application of wavelet decomposition method can effectively identify the interference source that can not be judged.