王婷婷, 边银菊, 张博. 2014: 地震与爆破的小波包识别判据研究. 地震学报, 36(2): 220-232. DOI: 10.3969/j.issn.0253-3782.2014.02.007
引用本文: 王婷婷, 边银菊, 张博. 2014: 地震与爆破的小波包识别判据研究. 地震学报, 36(2): 220-232. DOI: 10.3969/j.issn.0253-3782.2014.02.007
Wang Tingting, Bian Yinju, Zhang Bo. 2014: Recognition criteria of earthquakes and explosions based on wavelet packet analysis. Acta Seismologica Sinica, 36(2): 220-232. DOI: 10.3969/j.issn.0253-3782.2014.02.007
Citation: Wang Tingting, Bian Yinju, Zhang Bo. 2014: Recognition criteria of earthquakes and explosions based on wavelet packet analysis. Acta Seismologica Sinica, 36(2): 220-232. DOI: 10.3969/j.issn.0253-3782.2014.02.007

地震与爆破的小波包识别判据研究

Recognition criteria of earthquakes and explosions based on wavelet packet analysis

  • 摘要: 利用sym5小波包基函数对小震级天然地震和人工爆破波形进行4层小波包分解并绘制了时频谱图.通过时频谱图可直观得出, 爆破频率成分简单, 时频谱聚集性较好. 为寻求定量的识别指标, 综合P波和S波小波包变换结果, 提出并定义了P/S能量比. 分析识别效果较好的 P/S能量比判据得出爆破的P波主频集中在频段3.125—9.375 Hz处, 地震频率成分较复杂, S波在高频12.5—23.4375 Hz处也较发育, 在这些频段上, 爆破的P波与S波差异要大于地震的P波与S波差异. 作为小波包判据研究的补充, 文中也提取分析了P波的能量比与S波的能量比. 能量比判据识别结果表明, 人工爆破与天然地震的频率成分存在差异, 通过小波包变换能够提取有效的识别判据.

     

    Abstract: This paper uses sym5 wavelet packet basics function to decompose waveforms of small magnitude natural earthquakes and artificial explosions. Through spectrograms the differences of frequency components could be visually seen, the explosion frequency is simple and the aggregation of spectrogram is better than earthquake. Combining the wavelet packet transform results of P-wave and S-wave, the P/S energy ratio is defined so as to seek quantitative recognition indices. Analyses on the better classified P/S energy ratios show that the explosion’s energy of P mainly concentrates on the frequency band of 3.125—9.375 Hz, and the earthquake’s frequency are more complex, S are also developed at high frequency 12.5—23.4375 Hz, indicating that the differences between P-wave and S-wave of explosion are greater than natural earthquake in these frequency bands. As a supplement of wavelet packet criteria, we also extract and analyze the energy ratios of P and S waves. The results of energy ratio criteria show that earthquake and explosion have different frequency component and we can extract effective recognition criteria by wavelet packet transform.

     

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