首页|基于分形维数的高速铁路地震预警系统地震P波震相识别方法

基于分形维数的高速铁路地震预警系统地震P波震相识别方法

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为更好保障高速铁路的运营安全,高速铁路地震预警系统的实施十分必要.5级以下的小震事件占据地震事件的95％以上,提高高速铁路预警系统在小震震相识别的速度与精度能有效保障高铁安全运营.提出一种基于分形维数的地震震相识别算法,优化传统分形维数的计算方法,提高分形维数的计算速度.引入分形斜率曲线并划分为4个阶段,分析临界点的分形斜率特征,通过识别分形斜率极值时刻判断地震波精准到达时刻.提出的算法平均误差达到0.006 3 s,标准差达到0.043 8 s,满足高速铁路地震预警系统的时效性和准确度要求.
Seismic P-Wave Phase Identification Method for High-speed Railway Earthquake Early Warning System Based on Fractal Dimension
The implementation of high-speed railway earthquake early warning system can better guarantee the operation safety of high-speed railway.As small earthquakes with magnitude below 5 account for more than 95％of seismic events,improving the recognition speed and accuracy of high-speed railway early warning system in identifying small earthquake phases can effectively guarantee the safe operation of high-speed railways.In this paper,a P wave recognition algorithm based on fractal dimension was proposed to optimize the traditional calculation method of fractal dimension and improve the calculation speed of fractal dimension.The fractal slope curve was introduced and divided into four stages to analyze the fractal slope characteristics of critical points.The precise arrival time of seismic waves was determined by detecting the extreme moment of fractal slope.The proposed algorithm has an average error of 0.006 3 s and standard deviation of 0.043 8 s,which fully meets the requirements of timeliness and accuracy of earthquake warning system for high-speed railway.

high-speed railwayearthquake early warningP wave identificationshort time average/long time averageAkaike information criterion

杨长卫、张凯文、吴东升、张志方、张良、瞿立明

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西南交通大学土木工程学院,四川成都 610031

中国铁路武汉局集团有限公司,湖北武汉 430071

西南交通大学地球科学与环境工程学院,四川成都 611756

高速铁路 地震预警 P波识别 长时窗均值与短时窗均值之比 赤池信息法则

国家重点研发计划国家自然科学基金国家铁路局课题四川省自然科学基金

2018YFE020710052372343K2023-0402022NSFSC1086

2024

10.3969/j.issn.1001-8360.2024.01.018

铁道学报
中国铁道学会

铁道学报

CSTPCD北大核心
影响因子：0.9
ISSN：1001-8360
年,卷(期)：2024.46(1)
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