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A NEW METHOD OF IDENTIFYING GROUND-BASED ELECTROMAGNETIC ANOMALIES – CASE STUDY OF THE SICHAN LUSHAN 7.0 EARTHQUAKE

Han, Bing, Zhao, Gouge, Bi, Yaxin, Wang, Lifeng, Tang, Ji and Cheng, Yuanzhi (2014) A NEW METHOD OF IDENTIFYING GROUND-BASED ELECTROMAGNETIC ANOMALIES – CASE STUDY OF THE SICHAN LUSHAN 7.0 EARTHQUAKE. In: Dragon 3 symposium. ESA Communications. 8 pp, Chengdu, China. ESA SP-724. 8 pp. [Conference contribution]

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Abstract

Stereo-observation, being comprised of both ground-and space-based observations, is an important approach for likely making earthquake prediction to break through. The electromagnetic observation is considered as one of the most important measures in the stereo-observation, and should be one of the fields in which breakthrough is firstly and likely made and would be an effective device to obtain information for earthquake pre-warning. New techniques of alternating electromagnetic field observation, e.g., Controlled-Source Extremely Low Frequency (CSELF) and satellite observation, are gradually applied to the earthquake monitoring, which contain the more abundant information than those mainly observed in constant electric or magnetic field. This will increase the amount of recorded data greatly and inevitably require the robust techniques of data processing and analyzing. Previous analysis techniques mainly utilize the Fourier transform method for alternating electromagnetic field data, which cannot consider the information in time and frequency domains simultaneously. In this study we try to use the wavelet transform method to process alternating electromagnetic field data and carry out a case study, which aims to obtain the electromagnetic anomaly information in both frequency- and time-domains. The study is conducted on the data observed for 35 days during the strong aftershock period after the Lushan earthquake with Ms=7.0 in the Sichuan province in China. The preliminary results show that the wavelet transform method has an advantage and potential for identifying the electromagnetic anomalies relative to the earthquake events.

Item Type:Conference contribution (Paper)
Keywords:Electromagnetic data, Anomaly detection, Earthquake
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:38989
Deposited By: Dr Yaxin Bi
Deposited On:15 Nov 2017 15:08
Last Modified:15 Nov 2017 15:08

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