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不同采样率下四分量钻孔应变观测同震变化特征
引用本文:唐 磊,邱泽华,樊俊屹,罗自浩. 不同采样率下四分量钻孔应变观测同震变化特征[J]. 大地测量与地球动力学, 2022, 42(11): 1196-1201
作者姓名:唐 磊  邱泽华  樊俊屹  罗自浩
摘    要:
利用湟源台四分量钻孔应变观测的分钟值、1 sps、10 sps和100 sps四种不同采样率的观测数据,通过自检分析、同震应变阶分析和频谱分析等方法研究青海玛多M7.4地震同震变化特征。研究结果表明,分钟采样记录的地震波信息缺失严重,用分钟采样数据进行地震波初动、同震变化幅度等研究将会得到信度较低的结论;采样率越高,记录应变地震波信息的能力越强,但100 sps采样和10 sps采样结果相差不大,10 sps采样已能记录到比较全面的应变地震波信息;同震应变阶的变化性质和变化幅度与采样率无关;未来布设四分量钻孔应变仪时,建议应将采样率至少提高至1 sps。

关 键 词:四分量钻孔应变观测  采样率  同震变化  应变阶  频谱分析  

Characteristic Analysis of Coseismic Variation of 4-Component Borehole Strain Observation with Different Sampling Rates
TANG Lei,QIU Zehua,FAN Junyi,LUO Zihao. Characteristic Analysis of Coseismic Variation of 4-Component Borehole Strain Observation with Different Sampling Rates[J]. Journal of Geodesy and Geodynamics, 2022, 42(11): 1196-1201
Authors:TANG Lei  QIU Zehua  FAN Junyi  LUO Zihao
Abstract:
Using minute, 1 sps, 10 sps and 100 sps sampling rate observation data from a 4-component borehole strainmeter at Huangyuan station, we study the co-seismic variation of Maduo M7.4 earthquake in Qinghai by self-check analysis, co-seismic strain step analysis and spectrum analysis. The results show that the seismic wave information recorded by minute sampling is seriously lacking. If we use the minute value data to study the initial motion of seismic wave and the amplitude of co-seismic variation, we obtain a conclusion of low reliability. The higher the sampling rate, the stronger the ability to record strain seismic wave information, but the difference between 100 sps sampling and 10 sps sampling is not significant, and 10 sps sampling basically records more comprehensive strain seismic wave information. The variation property and amplitude of co-seismic strain steps are independent of sampling rate, and the minute sampling data can be used for related research. When the 4-component borehole strainmeter is set up in the future, the sampling rate should be increased to at least 1 sps.
Keywords:4-component borehole strainmeter  sampling rate  co-seismic variation  strain step  spectral analysis  
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