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高阶统计量及AIC方法在区域地震事件和直达P波初动识别中的应用
Detection of regional seismic events by high order statistics method and automatic identification of direct P-wave first motion by AIC method
【摘要】 利用高阶统计量(偏斜度和峰度)与赤池信息量准则(简称AIC)相结合,进行区域地震事件实时检测和P波初至精细识别的新方法研究,通过处理山东地震台网记录的地震波资料,结果表明:应用高阶统计量(偏斜度和峰度,尤其是峰度)能够有效识别地震事件,降低地震事件的错误报警率和漏报率;与人工识别震相到时结果相比,根据Ske-AIC、Kur-AIC震相自动识别方法得到的震相到时的平均绝对值误差小。
【Abstract】 Basing on high order statistics and AIC method,we put forward new methods for real-time detection of regional earthquake event and automatic identification of direct P-wave first motion,and apply it to process seismic data recorded by Shandong Seismic Network.The results show as follows:①The high order statistics method(skewness and kurtosis,kurtosis especially) effectively detect earthquake events,and may effectively reduce false alarm and missing report rates;②Compared with phase arrival time results in manual identification,average absolute error of phase arrival time in automatic identification based on Kur-AIC and SkeAIC method are(0.09±0.08)s and(0.06±0.14)s,respectively.
【Key words】 high order statistics； AIC； earthquake identification； phase identification；
- 【文献出处】 地震地磁观测与研究 ,Seismological and Geomagnetic Observation and Research , 编辑部邮箱 ,2013年Z3期
- 【分类号】P315
- 【被引频次】5
- 【下载频次】59