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利用 P 波到时检测的同步震级估计在地震预警系统中的应用。

A Synchronous Magnitude Estimation with P-Wave Phases' Detection Used in Earthquake Early Warning System.

机构信息

National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China.

Institute of Disaster Prevention, Sanhe 065201, China.

出版信息

Sensors (Basel). 2022 Jun 16;22(12):4534. doi: 10.3390/s22124534.

DOI:10.3390/s22124534
PMID:35746316
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9227699/
Abstract

How to estimate an earthquake's magnitude rapidly and accurately is a challenge for any earthquake early warning system. In order to reach a balance between accuracy and timeliness, a synchronous magnitude estimation method with P-wave phases' detection is proposed. In this method, the P-wave phases are detected by the changes of the signal-to-noise ratio (SNR) of the seismic records, where the SNRs are calculated by the short-term power and long-term power ratio (STP/LTP). Meanwhile, the variations of the SNR are applied to estimate the magnitude of the earthquake. By the statistics of some earthquake cases, a synchronous magnitude estimation model of the variation of the P-wave phases' SNR, the earthquake magnitude, and the hypocentral distance was built. Compared with some other magnitude estimation methods, the suggested method inherits the robustness of the STP/LTP method and is more accurate and rapid than the peak displacement (Pd) method.

摘要

如何快速、准确地估计地震震级是任何地震预警系统的挑战。为了在准确性和及时性之间取得平衡,提出了一种利用 P 波相检测的同步震级估计方法。在该方法中,通过地震记录的信噪比(SNR)变化来检测 P 波相,其中 SNR 通过短期功率和长期功率比(STP/LTP)计算。同时,SNR 的变化被应用于估计地震震级。通过对一些地震案例的统计,建立了 P 波相 SNR、地震震级和震源距变化的同步震级估计模型。与其他一些震级估计方法相比,所提出的方法继承了 STP/LTP 方法的稳健性,并且比峰值位移(Pd)方法更准确和快速。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/b4f5a1100744/sensors-22-04534-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/3c75f510bd8b/sensors-22-04534-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/ba4e1a039d1c/sensors-22-04534-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/b4f5a1100744/sensors-22-04534-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/704b58ad9d3e/sensors-22-04534-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/190486b8a0e6/sensors-22-04534-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/31169f9b3eb1/sensors-22-04534-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/0e69e50a1d8c/sensors-22-04534-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/3c75f510bd8b/sensors-22-04534-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/ba4e1a039d1c/sensors-22-04534-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/959d2f336fe3/sensors-22-04534-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b32f/9227699/440f16f5f34e/sensors-22-04534-g010.jpg
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