小波变换在地电场数据分析中的应用

Application of wavelet transform to the analysis of geoelectric field data

  • 摘要: 随着城镇化发展的加快, 上海的地电场观测受到来自周围环境噪声的影响日益严重, 这些噪声干扰对于地震前兆异常的分析判断带来很多不确定性. 本文主要探讨通过小波变换方法来分解地电场观测原始信号, 分析环境噪声对原始观测数据的影响强度. 利用异常信号的小波模值对比分析了滤波结果, 并通过绘制极化方位图检验了该方法在实际运用中的效果. 结果表明: 数字滤波方法能很好地去除日常干扰所带来的背景噪声, 对于重构的地电场信号, 也能较好地反映其原始信号变化特征; 滤波后的自然电场异常信号保留了原始信号中主要的变化特征, 并能反映其原始变化规律; 重构的地电场信号能够突出信号中异常信号极化方位角, 使极化方位收敛有利于实际运用.

     

    Abstract: As urbanization gets into faster development, geoelectric field observation is affected by the electric signals from artificial interferences in Shanghai. It is difficult to distinguish such signals from signals of earthquake precursors. In this paper, the original signals of geoelectric field are decomposed by wavelet transform, and the intensity of background noise interference to original observation data are analyzed. We made a comparison between the original signals and filtered signals by analyzing Morlet wavelet transform modulus of abnormal signals, and tested the filtering effect in practical application by drawing azimuthal polarization plot. The results indicate that ① the method has a good performance in filtering background noises and the reconstructed signals of geoelectric field can well reflect the characteristics of original signals; ② the filtered signals of spontaneous electric field retain the variation tendency of original signals; ③ the reconstructed signals of geoelectric field can highlight the polarization characteristics of geoelectirc field and make the convergent polarization azimuth favorable to practical application.

     

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