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Title:: Application Research on Automatic Identification of Annual Cycle Breaking Anomalies in the Fixed-point Deformation

作者:: 苑争一¹; 闫伟¹; 牛安福¹; 赵静¹; 高歌²; (1.中国地震台网中心,北京 100045; 2.新疆维吾尔自治区地震局,新疆乌鲁木齐 830011)

Author(s):: YUAN Zhengyi¹; YAN Wei¹; NIU Anfu¹; ZHAO Jing¹; GAO Ge²; (1.China Earthquake Networks Center,Beijing 100045,China)(2.Xinjiang Uygur Autonomous Region Eorthquake Agency,Urumqi 830011,Xinjiang,China)

Keywords:: Singular Spectrum Analysis(SSA); fixed-point deformation; assessment of earthquake forecast

摘要:: 基于奇异谱分析算法,以新疆东风煤矿钻孔倾斜EW分量和巴里坤水平摆倾斜NS分量为例,在去除典型干扰及长周期趋势变化的基础上,拟合观测资料背景年变序列。对于残差时间序列,结合震例进行动态R值检验,自动提取破年变异常特征时段,递归求解出了最高R值评分对应的异常判定准则。进而自动识别出具有最佳映震效能的破年变异常时段,实现了破年变异常判定的自动化和定量化,提高了前兆异常信号识别的可靠性和准确性。

Abstract:: Based on the Singular Spectrum Analysis(SSA)and the EW component of borehole tilt data in Xinjiang Dongfeng coal mine station,the NS component of quartz horizontal pendulum tiltmeter in Xinjiang Balikun station,this study has realized the fitting of the background annual variation information of the observation data by eliminating the typical interference and long period trend changes.The dynamic R value test was performed on the residual time series combined with the earthquake examples,and the annual cycle breaking anomalies are automatically extracted.At the same time,the anomaly determination criterion corresponding to the highest R value score is recursively solved.Then the annual cycle breaking periods are automatically identified with the best reflection performance on earthquakes,and the automation and quantification of the determination of anomalies are realized.Under the current level of knowledge and conditions,the reliability and accuracy of precursory abnormal signal recognition have been improved.