地震预警技术研究及应用
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摘要
地震预警可在破坏性地震发生后,破坏性地震波到来前,提供数秒至数十秒的预警时间,并采取相应应急处置措施,是近二十年来新发展起来的减轻地震损失、降低地震次生灾害、减少人员伤亡的有效手段。论文重点研究了满足地震预警时效性要求的震相自动精确捡拾、地震定位、震级确定、地震动场估计等地震预警地震基本参数和目标区工程地震参数的确定方法,方法均为实时持续的并考虑了在线运行的实用性,并以研究成果为技术支撑,以福建数字测震台网与实时传输强震台网为基础平台,初步构建了地震预警系统总体架构。本文主要工作概括如下:
(1)发展了一种能应用于地震预警的P波及S波震相多步精确捡拾方法,该方法综合应用目前最常用的STA/LTA、偏振分析和AIC方法,对P波及S波震相多步自动捡拾,提高了捡拾的适用性和稳定性;提出了一种基于有限先到台的Delaunay三角剖分干扰信号剔除方法,提高了事件触发捡拾的可靠性。应用福建数字地震台网数据,对方法进行了验证,结果表明此方法可以较好的应用于地震预警的P波触发捡拾及P波和S波精确到时自动捡拾。
(2)提出了一套应用于地震预警的实时持续定位方法,该方法充分应用有限信息,应用Voronoi台网剖分、S波与P波到时差圆及未到S波等待、偏振震中方位角、P波到时差双曲线和震中方位角等技术,考虑了不同震相到时对震源深度的不同反应及对定位的影响,针对不同的震相特点和震相到时顺序,在第一个台站接收到P波至前三台接收到P波并且第一台接收到S波的时间段内,把预警定位分成了6种情形,实时持续对地震进行定位。对于各种情形,用福建数字地震台网记录自动捡拾到的P波及S波震相进行了验证,其结果可以满足地震预警的需要。
(3)提出了一种基于P波首脉冲的有效累积上升脉冲宽度估计预警地震震级方法,其精度和目前最常用的卓越周期方法相当。为了提高震级确定的稳定性和精度,进一步提出了一种实时持续确定预警地震震级的方法,该方法通过实时仿真多频带多类型(加速度、速度和位移)记录,综合应用有限P波段各秒段(1-10s)的多种震级指示参数(幅值参数:加速度峰值、速度峰值、位移峰值及周期参数:卓越周期、Vmax/Amax、有效累积脉冲宽度)用人工神经元网络持续估计震级参数,考虑了各个参数间的非线性,综合考虑了P波所携带信息的多种特征,结果稳定可靠。应用日本KiK-net台网基岩强震记录对方法进行了验证,对单台记录P波到后1-10s段的持续震级均能得到较高的精度。
(4)提出了一种基于记录初始信息的后续地震动(PGA,PGV,PGD等)持续预测方法,原理与实时持续确定预警地震震级的方法大致相同,用人工神经元网络持续对后续峰值进行预测,该方法应用有限P波段(1-10s)持续预测后续最终地震动参数,可以直接应用于现地预警,结果稳定可靠;应用以上后续地震动预测结果,给出了一种地震动分布图持续预测方法,该方法可以持续确定区域地震动分布图,并随着预警地震参数的持续确定和有台站处后续峰值的持续预测,对地震动分布图进行实时持续估计。
(5)以研究成果为技术支撑,以福建数字测震台网与实时传输强震台网为基础平台,初步构建了地震预警系统总体架构并对地震预警技术的发展进行了展望。
Earthquake early warning (EEW) system provides a few seconds to tens of seconds of warning time for impending ground motions due to a large earthquake and allows for mitigation measures in the short term. It is a new technology and new measure for seismic hazard mitigation in last twenty years and has the potential to reduce fatalities, casualties, costs. This paper focus on some key technologies for EEW include automatic picking phase arrival precisely, earthquake location, magnitude determination, the strong motion maps estimation of earthquake early warning target area such as seismic principal parameters and engineering seismology parameters. Real-time online operation is considered for all algorithms. An EEW frame is constructed rely on the results of this paper and the Fujian Digital Seismograph Network. The contents are summarized as follows:
(1) A multi-step method has been developed for the automatic P-wave and S-wave accurate detection base on some common methods include STA/LTA, polarization analysis, and Akaike information criteria (AIC). The applicability and stability were improved. Also a new interference signal elimination method based the Delaunay triangulation has been developed and the detecting reliability was improved. We test our method on regional earthquake data from Fujian region. All results prove the expected low false rate, high timing accuracy and good detection probability for both P-wave and S-wave.
(2) A real-time continuous earthquake location method has been developed base on Voronoi diagram, hyperbolic curve of P-wave arrival time difference of two stations, circle of S-wave and P-wave arrival time difference and not yet arriving S-wave, and epicenter azimuth. The influence of focal depth for different seismic phase arrive time is also considered. From the time that the first P-wave arrived to the nearest station to the time that three stations had detected P-wave and the first station had detected the S-wave, six cases are classified and the location process is continuous. We test all case on regional earthquake data from Fujian region using automatic P-wave and S-wave detection results. An off-line test proves that the location results are satisfying for EEW.
(3) A new method to determinate the magnitude has been developed based on the effective cumulative rising width of first radial P-wave displacement pulse. As comparing with the most commonly used average‘predominant period’τc method it has the same precision. Farther for improving the precision and the stability for magnitude, another new real-time continuous method has been developed. Various period parameters and amplitude parameters for different frequency band include peak acceleration, peak velocity, peak displacement, predominant period, the ratio of peak velocity and peak acceleration Vmax/Amax, and effective cumulative rising width for every second after P-wave arrived were considered. All the parameters were synthesized using Artificial Neural Networks (ANN). So, various characters of every initial P-wave segment were considered synthetically and continuously. We test our method on the bedrock records of digital strong-motion seismograph of Japan (KiK-net). We find that the magnitude of even the single station for every second after the P-wave arrived is satisfying for EEW.
(4) As similar principle of magnitude real-time continuous determination, we have developed a method to estimate the imminent ground shaking (PGA, PGV, PGD) for every second after P-wave arrived based on ANN. It can be applied to on-site warning directly. Also we present a method to continuous evaluated ground motion maps using the result of estimated value exist station.
(5) An EEW frame is constructed rely on the study results of this paper and the Fujian digital Seismograph Network and the application of EEW in China is prospected.
(1)发展了一种能应用于地震预警的P波及S波震相多步精确捡拾方法,该方法综合应用目前最常用的STA/LTA、偏振分析和AIC方法,对P波及S波震相多步自动捡拾,提高了捡拾的适用性和稳定性;提出了一种基于有限先到台的Delaunay三角剖分干扰信号剔除方法,提高了事件触发捡拾的可靠性。应用福建数字地震台网数据,对方法进行了验证,结果表明此方法可以较好的应用于地震预警的P波触发捡拾及P波和S波精确到时自动捡拾。
(2)提出了一套应用于地震预警的实时持续定位方法,该方法充分应用有限信息,应用Voronoi台网剖分、S波与P波到时差圆及未到S波等待、偏振震中方位角、P波到时差双曲线和震中方位角等技术,考虑了不同震相到时对震源深度的不同反应及对定位的影响,针对不同的震相特点和震相到时顺序,在第一个台站接收到P波至前三台接收到P波并且第一台接收到S波的时间段内,把预警定位分成了6种情形,实时持续对地震进行定位。对于各种情形,用福建数字地震台网记录自动捡拾到的P波及S波震相进行了验证,其结果可以满足地震预警的需要。
(3)提出了一种基于P波首脉冲的有效累积上升脉冲宽度估计预警地震震级方法,其精度和目前最常用的卓越周期方法相当。为了提高震级确定的稳定性和精度,进一步提出了一种实时持续确定预警地震震级的方法,该方法通过实时仿真多频带多类型(加速度、速度和位移)记录,综合应用有限P波段各秒段(1-10s)的多种震级指示参数(幅值参数:加速度峰值、速度峰值、位移峰值及周期参数:卓越周期、Vmax/Amax、有效累积脉冲宽度)用人工神经元网络持续估计震级参数,考虑了各个参数间的非线性,综合考虑了P波所携带信息的多种特征,结果稳定可靠。应用日本KiK-net台网基岩强震记录对方法进行了验证,对单台记录P波到后1-10s段的持续震级均能得到较高的精度。
(4)提出了一种基于记录初始信息的后续地震动(PGA,PGV,PGD等)持续预测方法,原理与实时持续确定预警地震震级的方法大致相同,用人工神经元网络持续对后续峰值进行预测,该方法应用有限P波段(1-10s)持续预测后续最终地震动参数,可以直接应用于现地预警,结果稳定可靠;应用以上后续地震动预测结果,给出了一种地震动分布图持续预测方法,该方法可以持续确定区域地震动分布图,并随着预警地震参数的持续确定和有台站处后续峰值的持续预测,对地震动分布图进行实时持续估计。
(5)以研究成果为技术支撑,以福建数字测震台网与实时传输强震台网为基础平台,初步构建了地震预警系统总体架构并对地震预警技术的发展进行了展望。
Earthquake early warning (EEW) system provides a few seconds to tens of seconds of warning time for impending ground motions due to a large earthquake and allows for mitigation measures in the short term. It is a new technology and new measure for seismic hazard mitigation in last twenty years and has the potential to reduce fatalities, casualties, costs. This paper focus on some key technologies for EEW include automatic picking phase arrival precisely, earthquake location, magnitude determination, the strong motion maps estimation of earthquake early warning target area such as seismic principal parameters and engineering seismology parameters. Real-time online operation is considered for all algorithms. An EEW frame is constructed rely on the results of this paper and the Fujian Digital Seismograph Network. The contents are summarized as follows:
(1) A multi-step method has been developed for the automatic P-wave and S-wave accurate detection base on some common methods include STA/LTA, polarization analysis, and Akaike information criteria (AIC). The applicability and stability were improved. Also a new interference signal elimination method based the Delaunay triangulation has been developed and the detecting reliability was improved. We test our method on regional earthquake data from Fujian region. All results prove the expected low false rate, high timing accuracy and good detection probability for both P-wave and S-wave.
(2) A real-time continuous earthquake location method has been developed base on Voronoi diagram, hyperbolic curve of P-wave arrival time difference of two stations, circle of S-wave and P-wave arrival time difference and not yet arriving S-wave, and epicenter azimuth. The influence of focal depth for different seismic phase arrive time is also considered. From the time that the first P-wave arrived to the nearest station to the time that three stations had detected P-wave and the first station had detected the S-wave, six cases are classified and the location process is continuous. We test all case on regional earthquake data from Fujian region using automatic P-wave and S-wave detection results. An off-line test proves that the location results are satisfying for EEW.
(3) A new method to determinate the magnitude has been developed based on the effective cumulative rising width of first radial P-wave displacement pulse. As comparing with the most commonly used average‘predominant period’τc method it has the same precision. Farther for improving the precision and the stability for magnitude, another new real-time continuous method has been developed. Various period parameters and amplitude parameters for different frequency band include peak acceleration, peak velocity, peak displacement, predominant period, the ratio of peak velocity and peak acceleration Vmax/Amax, and effective cumulative rising width for every second after P-wave arrived were considered. All the parameters were synthesized using Artificial Neural Networks (ANN). So, various characters of every initial P-wave segment were considered synthetically and continuously. We test our method on the bedrock records of digital strong-motion seismograph of Japan (KiK-net). We find that the magnitude of even the single station for every second after the P-wave arrived is satisfying for EEW.
(4) As similar principle of magnitude real-time continuous determination, we have developed a method to estimate the imminent ground shaking (PGA, PGV, PGD) for every second after P-wave arrived based on ANN. It can be applied to on-site warning directly. Also we present a method to continuous evaluated ground motion maps using the result of estimated value exist station.
(5) An EEW frame is constructed rely on the study results of this paper and the Fujian digital Seismograph Network and the application of EEW in China is prospected.
引文
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