小波极大值方法及其在电磁异常信号提取中的应用

小波极大值法作为一种数据挖掘技术已经受到关注,并在地震科学研究领域开始进行应用研究。它能在长时间的观测数据中快速提取出不同时间、不同频率的有关异常信息。文中介绍了如何应用小波极大值法提取电磁场异常信息,即利用连续小波变换计算小波系数,计算各尺度小波系数的极大值,结合表征信号奇异性的Lipschitz指数分析异常的真实性,进而研究极大值在时间分布上的特点或规律,捕捉有关的电磁异常现象。利用该方法对2013年4月20日四川芦山7.0级地震后35d的连续观测的电磁场数据进行了分析,发现存在3次电磁场异常,探讨了这些异常可能与地震活动性之间存在的关系。尽管用这种方法尚不能确定发现的电磁场异常现象与地震有某种特定的关系,但是证明了小波极大值方法在连续观测数据中提取电磁异常现象的有效性。

WAVELET MAXIMA METHOD IN IDENTIFYING SINGULARITIES IN ELECTROMAGNETIC SIGNAL

Wavelet maxima method as a kind of data mining method has been applied to earthquake science research, which gives us a direct way to identify the singularities of different time and frequencies in the long time observations. This paper introduces how to identify the electromagnetic anomalies using the wavelet maxima, i.e., the wavelet coefficients are calculated by using continuous wavelet transform and then calculate the maximum value of wavelet coefficients in each scale and identify the singularities associated with the earthquake. The identified singularities are further examined by Lipschitz-exponent α. The proposed method has been employed using the 35 days' data of the electromagnetic field recorded in Baosheng station in Sichuan after the Lushan M_S7.0 earthquake, and three electromagnetic anomalies are collected, then, the relationships between the electromagnetic anomalies and the earthquakes are discussed. This method cannot give a certain relationship between the electromagnetic anomaly and earthquake, but it proves the method's effectiveness in extracting the electromagnetic anomaly in continuous observation data.