强噪声环境下基于信噪比的地震P波到时自动提取方法

付继华, 王旭, 李智涛, 谭巧, 王建军. 2019. 强噪声环境下基于信噪比的地震P波到时自动提取方法. 地球物理学报, 62(4): 1405-1412, doi: 10.6038/cjg2019L0745
引用本文: 付继华, 王旭, 李智涛, 谭巧, 王建军. 2019. 强噪声环境下基于信噪比的地震P波到时自动提取方法. 地球物理学报, 62(4): 1405-1412, doi: 10.6038/cjg2019L0745
FU JiHua, WANG Xu, LI ZhiTao, TAN Qiao, WANG JianJun. 2019. Automatic picking up earthquake's P waves using signal-to-noise ratio under a strong noise environment. Chinese Journal of Geophysics (in Chinese), 62(4): 1405-1412, doi: 10.6038/cjg2019L0745
Citation: FU JiHua, WANG Xu, LI ZhiTao, TAN Qiao, WANG JianJun. 2019. Automatic picking up earthquake's P waves using signal-to-noise ratio under a strong noise environment. Chinese Journal of Geophysics (in Chinese), 62(4): 1405-1412, doi: 10.6038/cjg2019L0745

强噪声环境下基于信噪比的地震P波到时自动提取方法

  • 基金项目:

    国家自然科学基金(41631073,41874019)和中央级公益性科研院所基本科研业务专项资助(JDZ2017-19)共同资助

详细信息
    作者简介:

    付继华, 男, 博士, 副研究员, 主要从事精密测量与智慧系统研究.E-mail:fujh@email.eq-icd.cn

  • 中图分类号: P315

Automatic picking up earthquake's P waves using signal-to-noise ratio under a strong noise environment

  • 大数据量、强噪声环境给地震P波到时的自动提取带来很大挑战.针对此问题,本文通过构建特殊的特征函数,建立SNR与STA/LTA的内在联系,提出两种基于SNR的地震P波到时自动提取方法,即基于SNR的STA/LTA方法与基于SNR的综合方法.这两种方法分别是运用SNR概念对传统STA/LTA方法和STA/LTA与AIC综合方法的改进.仿真分析结果表明:对于弱噪声环境(10 dB)和一般噪声环境(6 dB),本文方法较传统STA/LTA方法对地震P波到时提取的准确度更高;而对于强噪声环境(3 dB),本文方法仍能准确提取地震P波到时,而传统STA/LTA方法则出现了较大的误判率(10%)与漏判率(65%).本文方法为STA/LTA赋予了明确的物理意义,使其阈值的选取建立在严密的数学推导之上.另外,本文方法在进行地震P波到时自动提取的同时,兼具数据预处理功能,无需额外的基线校正或高通滤波,因而具有较好的实时性.

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  • 图 1 

    STA/LTA方法示意图

    Figure 1. 

    Schematic diagram of the STA/LTA method

    图 2 

    信噪比与长短窗相对功率比的关系框图

    Figure 2. 

    Relation block diagram of the SNR and the relative power ratio of long and short sliding windows

    图 3 

    AIC计算窗口示意图

    Figure 3. 

    AIC′s calculation window

    图 4 

    一组强噪声环境下地震P波自动提取的结果

    Figure 4. 

    Automatic picking of seismic P waves under strong background noise

    图 5 

    余震记录13的原始记录与两种STA/LTA值

    Figure 5. 

    Aftershock No.13 and its STA/LTAs

    表 1 

    不同背景噪声下地震P波自动提取统计表

    Table 1. 

    Automatic picking results of seismic P waves under different background noise

    方法 SNR/dB 平均偏差/s 标准偏差/s 误判率/% 漏判率/%
    传统STA/LTA 10 0.113 0.039 0 0
    6 0.240 0.122 5 15
    3 0.227 0.049 10 65
    基于SNR的STA/LTA 10 0.072 0.035 0 0
    6 0.138 0.036 0 0
    3 0.238 0.091 0 0
    基于SNR的综合法 10 0.020 0.007 0 0
    6 0.012 0.020 0 0
    3 0.036 0.061 0 0
    下载: 导出CSV

    表 2 

    汶川余震P波自动提取结果

    Table 2. 

    Automatic P waves′ picking results for the Wenchuan aftershocks

    序号 台站编码 人工结果/s 基于SNR的STA/LTA方法/s 基于SNR的综合方法/s
    1 JMG 4.997 5.05 5.02
    2 PWU 5.001 5.01 5.01
    3 QCH 5.000 4.98 4.96
    4 JMG 5.001 5.02 4.99
    5 MXI 4.999 5.01 5.01
    6 PWU 4.998 5.03 5.02
    7 QCH 5.001 5.03 5.02
    8 JJS 4.999 5.27 4.94
    9 JMG 4.997 4.93 4.91
    10 PWU 5.002 5.01 5.01
    11 QCH 5.005 5.05 5.03
    12 JJS 5.002 5.23 4.98
    13 JMG 5.003 5.07 4.97
    14 PWU 5.002 5.06 4.95
    15 QCH 5.003 5.09 4.94
    16 JMG 4.999 5.23 4.62
    17 PWU 4.998 5.01 5.00
    18. QCH 4.997 5.20 5.01
    19 QCH 4.999 5.10 5.03
    20 QCH 4.996 5.02 5.01
    21 JMG 5.004 5.06 5.03
    22 JMG 4.996 5.01 4.98
    23 JMG 4.996 5.02 5.00
    24 JMG 5.006 5.07 5.01
    25 PWU 5.004 5.03 5.02
    26 PWU 5.003 5.03 5.02
    27 PWU 5.001 5.02 5.01
    28 PWU 5.004 5.03 5.02
    29 QCH 4.998 5.01 5.01
    30 QCH 5.004 5.00 4.99
    平均偏差/s 0.056 -0.017
    标准偏差/s 0.078 0.075
    下载: 导出CSV

    表 3 

    汶川余震P波的SNR估计

    Table 3. 

    Estimated SNRs for Wenchuan aftershocks′ P waves

    序号 台站编码 基于SNR的STA/LTA最大值 P波的SNR最大值/dB
    1 JMG 9.402 21.5
    2 PWU 9.996 43.5
    3 QCH 9.901 29.5
    4 JMG 9.860 28.0
    5 MXI 9.991 40.0
    6 PWU 9.791 26.2
    7 QCH 9.873 28.4
    8 JJS 7.126 13.3
    9 JMG 9.859 28.0
    10 PWU 9.933 31.2
    11 QCH 9.647 23.9
    12 JJS 5.432 9.9
    13 JMG 6.772 12.5
    14 PWU 8.336 16.4
    15 QCH 7.844 15.0
    16 JMG 6.229 11.4
    17 PWU 9.965 34.1
    18. QCH 8.314 16.4
    19 QCH 9.034 19.2
    20 QCH 9.916 30.3
    21 JMG 9.980 36.5
    22 JMG 9.301 20.7
    23 JMG 9.880 28.7
    24 JMG 8.644 17.5
    25 PWU 9.955 33.0
    26 PWU 9.231 20.3
    27 PWU 9.984 37.5
    28 PWU 9.703 24.7
    29 QCH 9.995 42.6
    30 QCH 9.995 42.6
    下载: 导出CSV
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出版历程
收稿日期:  2017-12-06
修回日期:  2019-01-22
上线日期:  2019-04-05

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