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高阶统计量和AIC方法在区域地震事件和直达P波初动自动识别方面的应用
Detection of regional seismic events by high order statistics method and automatic identification of direct P-wave first motion by AIC method
- DOI:
- 作者:
- 赵大鹏1) 刘希强2) 刘尧兴1) 王志铄1) 赵晖1) 张亚琳1)
- 作者单位:
- 1) 中国郑州 450016 河南省地震局 2) 中国济南 250014 山东省地震局
- 关键词:
- 高阶统计量；AIC；地震事件识别；震相识别
high order statistics；AIC；earthquake identification；phase identification
- 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较小。
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 Ske-AIC method are (0.09 0.08) s and (0.06 0.14) s， respectively
