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Enhancing earthquake signal based on variational mode decomposition and S-G filter
Journal of Seismology ( IF 1.6 ) Pub Date : 2020-08-14 , DOI: 10.1007/s10950-020-09948-x
Tara P. Banjade , Jiong Liu , Haishan Li , Jianwei Ma

The precise estimation of associated parameters for microseismic and earthquake signals is a challenging task due to the presence of background noise. Important parameters to analyze earthquake signals such as peak ground acceleration, velocity, displacement, and P, S-wave arrival time are affected by noise. In this study, we propose a seismic data denoising algorithm by combining variational mode decomposition (VMD) and Savitzky-Golay (SG) filter. The method first employs a VMD technique that disintegrates the original signal into band-limited intrinsic mode functions. The modes that are contaminated with high-frequency noise are selected and smoothed by the SG filter. An important advantage of SG filters is their ability to retain the shape of data with high frequency. To observe the effect of noise, PPHASEPICKER is applied to the signal provided by the proposed denoising method. As the fundamental constituent of the earthquake accelerogram is displacement, we performed an experiment to expose the effect of noise and different denoising techniques on the displacement component. The results of synthetic data and real data from the Nepal 2015 earthquake show the enhancement of signal-to-noise ratio while preserving the significant features of the displacement component and onset time arrival accuracy, in comparison with some existing techniques.



中文翻译:

基于变分分解和SG滤波的地震信号增强

由于背景噪声的存在,精确估计微地震和地震信号的相关参数是一项艰巨的任务。诸如峰值地面加速度,速度,位移以及P,S波到达时间之类的用于分析地震信号的重要参数会受到噪声的影响。在这项研究中,我们提出了一种结合变分模式分解(VMD)和Savitzky-Golay(SG)滤波器的地震数据去噪算法。该方法首先采用VMD技术,该技术将原始信号分解为带限本征模式函数。SG滤波器选择并平滑了被高频噪声污染的模式。SG滤波器的一个重要优点是它们能够以高频率保留数据形状。为了观察噪声的影响,P PH A S E P I C K E R应用于所提出的降噪方法所提供的信号。由于地震加速度图的基本组成是位移,因此我们进行了一项实验,以揭示噪声和不同的降噪技术对位移分量的影响。与一些现有技术相比,尼泊尔2015年地震的综合数据和真实数据的结果表明,信噪比得到了增强,同时保留了位移分量和起始时间到达精度的重要特征。

更新日期:2020-08-14
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