An AETA Electromagnetic Disturbance Anomaly Extraction Method based on Sample Entropy

For the multi-component seismic monitoring system AETA's electromagnetic disturbance (ED) data, an outlier extraction method is proposed based on sample entropy. Sample entropy can reflect the possibility of new information in the time series. Sample entropy algorithm is utilized for processing the electromagnetic disturbance data to figure out the sample entropy sequence in days. Then sliding quartile method is used to obtain the outlier sequence by calculating the abnormal index of sample entropy sequence. The experiment result in Yibin Ms 6.0 earthquake and superposed epoch analysis demonstrate that the method can detect the outlier and have the ability to reflect earthquake.