变分模态分解在地震事件检测中的应用

Esteban Proaño, D. Benítez, R. Lara-Cueva, M. Ruiz
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引用次数: 5

摘要

在本文中,我们研究了用变分模态分解(VMD)对厄瓜多尔Cotopaxi火山地震信号进行分析。本文提出了VMD方法作为一种降噪方法,以提高地震事件的检测和起止点的识别。相对于之前研究的方法,VMD方法的主要优点是它在降低噪声和区分信号所需的特征数量方面具有鲁棒性。初步分析表明,由于得到的地震事件模态存在较大差异,将VMD应用于地震信号后,可以识别出火山构造地震和长周期地震等地震事件,因此该分解方法也可以用于提取特征,用于自动分类器。进一步的观察表明,用于获取信号模态的相同过程也可以应用于使用固定大小的窗口和幅度阈值来检测事件的存在,数值结果表明获得事件起始点和结束点的精度为99.26%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Use of Variational Mode Decomposition for Seismic Event Detection
In this paper, we investigate the use of Variational Mode Decomposition (VMD) for the analysis of seismic signals obtained from the Cotopaxi Volcano in Ecuador. The VMD method is proposed here as a method for noise attenuation to improve the event detection and the identification of the starting and end points of seismic events. The main advantage of the VMD method over previous studied methods is its robustness for reducing noise and the number of features necessary to distinguish amongst the signals. Preliminary analysis shows that seismic events such as volcano-tectonic (VT) earthquakes, and long-period (LP) events, can be identified after applying the VMD to the seismic signal due to the fact that the modes obtained are considerably different between these types of seismic events, therefore this decomposition could also be used to extract features for an automatic classifier. Further observations show that the same process used for obtaining the modes of the signal can also be applied to detect the presence of events using a fixed-size window and an amplitude threshold, the numerical results show a 99.26% accuracy for obtaining the events onset and ending points.
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