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《Progress in Geophysics》 2011-04
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A study on seismic signal HHT features extraction and SVM recognition of earthquake and explosion

BI Ming-xia~(1,3),HUANG Han-ming~(1*),BIAN Yin-ju~2,LI Rui~1,CHEN Yin-yan~1,ZHAO Jing~1(1.College of Computer and Information Engineering,Guangxi Normal University,Guilin 541004,China;2.Institute of Geophysics,China Seismological Bureau,Beijing 100081,China;3.Secondary Vocational School of Qingdao Development Zone,Qingdao 266500,China)  
Earthquake and explosion are nonlinear signals originating from non-stationary process.However, traditional signal analysis techniques are only suitable to linear and stationary signals.This paper describeds an attempt to extract discriminative seismic wave features from earthquake and explosion recorded signals based upon Hilbert-Huang Transform (HHT).By Empirical Mode Decomposition (EMD)original complex seismic signals are reduced to about ten intrinsic mode function components (IMF).In the first three IMF,extract their respective maximum amplitude s period (T_(Amax))and average cepstrum values(C_(ave))as signals features.The features data matrix of 1583 lines and 6 rows extracted from these signals by the above mentioned extraction method.This sample was partitioned by strict mode recognition samples,and was recognized by Support Vector Classifier (SVC).About the model which was got from part of the collection of the samples,the prediction capability is very effective,correct recognition rate reached about 75%~-94%.This result shows that maximum amplitude s period (TA_(Amax))and average cepstrum values (C_(ave))of EMD components of original seismic wave are effective features for discriminating earthquake and explosion.
【Fund】: 地震行业科研专项基金(200808()(13)项目资助
【CateGory Index】: O643.223;P315
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