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Titel |
Local Earthquake Onset Detection Based on Short Time Fourier Transform |
VerfasserIn |
Nasim Karamzadeh, Peter Voss, Gholam Javan Doloei, Alireza Moghaddamjoo |
Konferenz |
EGU General Assembly 2011
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Medientyp |
Artikel
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Sprache |
Englisch
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 13 (2011) |
Datensatznummer |
250050665
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Zusammenfassung |
The existence of the large number of seismographs in Iran and necessity of a fast and precise
analysis of them motivates the implementation of an automated procedure to analyze the
data from these seismographs. In this study we introduce a method of automatic
P-phase picking for analyzing local earthquakes in Iran. The proposed algorithm is
categorized as a time-frequency domain version of the well-known STA/LTA method,
since it investigates the power in a short term window versus the power in a long
term window of a time-frequency representation of a seismogram. In the proposed
method Short Time Fourier Transform is calculated along the seismic signal using the
Gaussian time window. The total power in the selected frequency band is calculated
for each time window and the produced time series is regarded as a characteristic
function to which STA/LTA picking algorithm is applied and P phase arrival time is
determined.
The performance of our method is evaluated using two databases of more than
100 local events and the P-phases detected by the algorithm are compared with
those reported in the databases. The first data set included 118 very minor ( 2 -¤
mb < 3) local events which have been selected from aftershocks of the Zarand,
February 22, 2005, mb = 6.4 earthquake recorded by the temporary broadband stations
installed by International Institute of Earthquake Engineering and Seismology. The
second data set consist of 100 very minor local events (2 -¤ mb < 3) gathered by the
Iranian National Seismic Network (INSN). These earthquakes occurred within
the Iranian plateau during 2005 and 2006. The results show that the mean value
and standard deviation of time differences between manually and automatically
determined onset times are both less than 0.3 s for both data sets. Accordingly the
proposed phase picking algorithm can be used to determine P phase onset time
automatically on local events recorded at Iranian Plateau, e.g. in aftershock analysis. |
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