Signal detection based on empirical mode decomposition and Teager-Kaiser energy operator and its application to P and S wave arrival time detection in seismic signal analysis

被引:19
作者
Kirbas, Ismail [1 ]
Peker, Musa [2 ]
机构
[1] Mehmet Akif Ersoy Univ, Fac Engn & Architecture, Dept Comp Engn, Burdur, Turkey
[2] Mugla Sitki Kocman Univ, Dept Informat Syst Engn, Mugla, Turkey
关键词
Empirical mode decomposition; Seismic wave analysis; Teager-Kaiser energy operator; P and S wave detection; Seismic wave arrival time detection; ARTIFICIAL NEURAL-NETWORK; HIGHER-ORDER STATISTICS; AUTOMATIC PICKING; EVENT DETECTION; PHASE PICKING; 1ST ARRIVALS; IDENTIFICATION; RECOGNITION; SEISMOGRAMS; NOISE;
D O I
10.1007/s00521-016-2333-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Determining P and S wave arrival times while minimizing noise is a major problem in seismic signal analysis. Precise determination of earthquake onset arrival timing, determination of earthquake magnitude, and calculation of other parameters that can be used to make more accurate seismic maps are possible with the detection of these waves. Experts try to determine these waves by manual analysis. But this process is time-consuming and painful. In this study, a new method that enables the determination of P and S wave arrival times in noisy recordings is recommended. This method is based on the hybrid usage of empirical mode decomposition and Teager-Kaiser energy operator algorithms. The results show that the proposed system gives effective results in the automatic detection of P and S wave arrival times. Promisingly, the recommended system might serve as a novel and powerful candidate for the effective detection of P and S wave arrival time.
引用
收藏
页码:3035 / 3045
页数:11
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