Time domain feature extraction technique for earth’s electric field signal prior to the earthquake

Earthquake is one of the most destructive of natural disasters that killed many people and destroyed a lot of properties. By considering these catastrophic effects, it is highly important of knowing ahead of earthquakes in order to reduce the number of victims and material losses. Earth's elect...

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Bibliographic Details
Main Authors: Astuti , Winda, Sediono, Wahju, Akmeliawati, Rini, Salami, Momoh Jimoh Emiyoka
Format: Conference or Workshop Item
Language:English
Published: 2013
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Online Access:http://irep.iium.edu.my/30788/1/p.icom.2013.astuti.Time_Domain_Feature_Extraction_Technique.2017.pdf
http://irep.iium.edu.my/30788/
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
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Summary:Earthquake is one of the most destructive of natural disasters that killed many people and destroyed a lot of properties. By considering these catastrophic effects, it is highly important of knowing ahead of earthquakes in order to reduce the number of victims and material losses. Earth's electric field is one of the features that can be used to predict earthquakes (EQs), since it has significant changes in the amplitude of the signal prior to the earthquake. This paper presents a detailed analysis of the earth’s electric field due to earthquakes which occurred in Greece, between January 1, 2008 and June 30, 2008. In that period of time, 13 earthquakes had occurred. 6 of them were recorded with magnitudes greater than Ms=5R (5R), while 7 of them were recorded with magnitudes greater than Ms=6R (6R). Time domain feature extraction technique is applied to analyze the 1st significant changes in the earth’s electric field prior to the earthquake. Two different time domain feature extraction techniques are applied in this work, namely Simple Square Integral (SSI) and Root Mean Square (RMS). The 1st significant change of the earth's electric field signal in each of monitoring sites is extracted using those two techniques. The feature extraction result can be used as input parameter for an earthquake prediction system.