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首页> 外文期刊>Computers & geosciences >Identifying P phase arrival of weak events: The Akaike Information Criterion picking application based on the Empirical Mode Decomposition
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Identifying P phase arrival of weak events: The Akaike Information Criterion picking application based on the Empirical Mode Decomposition

机译：识别弱事件的P相到达：基于经验模态分解的Akaike信息准则选择应用程序

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摘要

Seismic P phase arrival picking of weak events is a difficult problem in seismology. The algorithm proposed in this research is based on Empirical Mode Decomposition (EMD) and on the Akaike Information Criterion (AIC) picker. It has been called the EMD-AIC picker. The EMD is a self-adaptive Signal decomposition method that not only improves Signal to Noise Ratio (SNR) but also retains P phase arrival information. Then, P phase arrival picking has been determined by applying the AIC picker to the selected main Intrinsic Mode Functions (IMFs). The performance of the EMD-AIC picker has been evaluated on the basis of 1938 micro-seismic signals from the Yongshaba mine (China). The P phases identified by this algorithm have been compared with manual pickings. The evaluation results confirm that the EMD-AIC pickings are highly accurate for the majority of the micro-seismograms. Moreover, the pickings are independent of the kind of noise. Finally, the results obtained by this algorithm have been compared to the wavelet based Discrete Wavelet Transform (DWT)-AIC pickings. This comparison has demonstrated that the EMD-AIC picking method has a better picking accuracy than the DWT-AIC picking method, thus showing this method's reliability and potential.
机译：弱事件的地震P期到达选择是地震学中的一个难题。本研究中提出的算法基于经验模式分解（EMD）和Akaike信息准则（AIC）选择器。它被称为EMD-AIC选择器。 EMD是一种自适应信号分解方法，不仅可以改善信噪比（SNR），而且可以保留P相到达信息。然后，已通过将AIC选择器应用于所选的主要本征模式功能（IMF）来确定P相到达选择。 EMD-AIC采集器的性能已根据来自永沙坝矿（中国）的1938年微地震信号进行了评估。该算法确定的P相已与人工采摘进行了比较。评估结果证实，EMD-AIC采集对于大多数微地震图都是高度准确的。而且，采摘与噪声的种类无关。最后，将该算法获得的结果与基于小波的离散小波变换（DWT）-AIC拾取进行了比较。该比较表明，EMD-AIC拣选方法比DWT-AIC拣选方法具有更好的拣选精度，从而显示了该方法的可靠性和潜力。

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