基于主成分方法分析2013年甘肃岷县漳县6.6级地震前地磁日变化异常

doi:10.12196/j.issn.1000-3274.2022.01.009

摘要/Abstract

摘要： 选用2013—2014年兰州台、天水台、寺滩台3个台站地磁垂直分量分钟值数据, 利用调和分析剔除1~4次地磁日变化谐波成分, 在此基础上对3个台站地磁Z分量数据进行主成分分析, 计算结果显示: 2013年7月22日岷县漳县6.6级地震前, 最小的第三主成分在2013年4月20日至6月10日出现明显的增强变化, 超出阈值, 异常持续50 d左右; 同时, 在信号的子空间中特征矢量的方向也出现同步的异常扰动, 震后恢复到原来的水平, 其他时段第三主成分未出现类似变化。据此认为, 这些异常信号与2013年岷县漳县6.6级地震相关。研究结果表明, PCA方法对地震电磁异常的提取是有效的。

关键词: 主成分分析, 地磁日变化, 调和分析, 地磁异常

Abstract: In this paper, the geomagnetic vertical component data of Lanzhou, Tianshui and Sitan stations from 2013 to 2014 have been selected, and the harmonic components of 1~4 geomagnetic daily variation are eliminated by harmonic analysis. On this basis, the geomagnetic Z component data of three stations are analyzed by principal component analysis (PCA). The results show that the third principal component shows an apparent increase from April 20 to June 10, 2013, the abnormal precursory exceeds the threshold and lasts for about 50 days before the Minxian—Zhangxian M6.6 earthquake on July 22, 2013. Meanwhile, the eigenvetctor direction in the signal subspace also appears synchronous abnovmal disturbance, which recovers to the original level after the earthquake. These features are likely to be correlated with the 2013 Minxian—Zhangxian M_S6.6 earthquake, and it means that the PCA method is effective for detection of seismomagnetic anomalies.

Key words: PCA, Geomagnetic daily variation, Harmonic analysis, Geomagnetic anomaly

中图分类号:

P315.7

李军辉, 何康, 王燚坤, 汪小厉. 基于主成分方法分析2013年甘肃岷县漳县6.6级地震前地磁日变化异常[J]. 地震, 2022, 42(1): 122-132.

LI Jun-hui, HE Kang, WANG Yi-kun, WANG Xiao-li. Principal Component Analysis of Geomagnetic Daily Variation before the 2013 Minxian—Zhangxian M_S6.6 Earthquake, Gansu, China[J]. EARTHQUAKE, 2022, 42(1): 122-132.

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