Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment Characteristic
The moment of P-wave arrival can provide us with many information about the nature of a seismic event. Without adequate knowledge regarding the onset moment, many properties of the events related to location, polarization of P-wave, and so forth are impossible to receive. In order to save time requi...
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          | Published in | Shock and vibration Vol. 2016; no. 2016; pp. 1 - 6 | 
|---|---|
| Main Authors | , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Cairo, Egypt
          Hindawi Publishing Corporation
    
        01.01.2016
     John Wiley & Sons, Inc Wiley  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 1070-9622 1875-9203 1875-9203  | 
| DOI | 10.1155/2016/4051701 | 
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| Abstract | The moment of P-wave arrival can provide us with many information about the nature of a seismic event. Without adequate knowledge regarding the onset moment, many properties of the events related to location, polarization of P-wave, and so forth are impossible to receive. In order to save time required to indicate P-wave arrival moment manually, one can benefit from automatic picking algorithms. In this paper two algorithms based on a method finding a regime switch point are applied to seismic event data in order to find P-wave arrival time. The algorithms are based on signals transformed via a basic transform rather than on raw recordings. They involve partitioning the transformed signal into two separate series and fitting logarithm function to the first subset (which corresponds to pure noise and therefore it is considered stationary), exponent or power function to the second subset (which corresponds to nonstationary seismic event), and finding the point at which these functions best fit the statistic in terms of sum of squared errors. Effectiveness of the algorithms is tested on seismic data acquired from O/ZG “Rudna” underground copper ore mine with moments of P-wave arrival initially picked by broadly known STA/LTA algorithm and then corrected by seismic station specialists. The results of proposed algorithms are compared to those obtained using STA/LTA. | 
    
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| AbstractList | The moment of P-wave arrival can provide us with many information about the nature of a seismic event. Without adequate knowledge regarding the onset moment, many properties of the events related to location, polarization of P-wave, and so forth are impossible to receive. In order to save time required to indicate P-wave arrival moment manually, one can benefit from automatic picking algorithms. In this paper two algorithms based on a method finding a regime switch point are applied to seismic event data in order to find P-wave arrival time. The algorithms are based on signals transformed via a basic transform rather than on raw recordings. They involve partitioning the transformed signal into two separate series and fitting logarithm function to the first subset (which corresponds to pure noise and therefore it is considered stationary), exponent or power function to the second subset (which corresponds to nonstationary seismic event), and finding the point at which these functions best fit the statistic in terms of sum of squared errors. Effectiveness of the algorithms is tested on seismic data acquired from O/ZG “Rudna” underground copper ore mine with moments of P-wave arrival initially picked by broadly known STA/LTA algorithm and then corrected by seismic station specialists. The results of proposed algorithms are compared to those obtained using STA/LTA. | 
    
| Audience | Academic | 
    
| Author | Obuchowski, Jakub Koziarz, Eugeniusz Wylomanska, Agnieszka Zimroz, Radoslaw Sokolowski, Jakub  | 
    
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| CitedBy_id | crossref_primary_10_1051_e3sconf_20182900019 crossref_primary_10_1155_2019_5961073 crossref_primary_10_1007_s42452_021_04330_z  | 
    
| Cites_doi | 10.1785/0120000026 10.1785/BSSA0680051521 10.1007/s10950-006-2296-6 10.1016/s0031-9201(99)00007-2 10.1016/j.dsp.2013.12.009 10.1002/jgrb.50274 10.1016/j.dsp.2008.08.003 10.1007/978-1-4612-1694-0_15 10.1785/BSSA0870061598 10.1016/s0031-9201(99)00054-0 10.1785/BSSA0850010308 10.1137/0111030 10.1785/BSSA0740020361 10.1785/0120020241 10.1090/qam/10666 10.5506/aphyspolb.44.1015 10.1155/2016/8453426 10.1785/BSSA0880010095 10.1016/j.cageo.2010.05.022  | 
    
| ContentType | Journal Article | 
    
| Copyright | Copyright © 2016 Jakub Sokolowski et al. COPYRIGHT 2016 John Wiley & Sons, Inc. Copyright © 2016 Jakub Sokolowski et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.  | 
    
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| Snippet | The moment of P-wave arrival can provide us with many information about the nature of a seismic event. Without adequate knowledge regarding the onset moment,... | 
    
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| SubjectTerms | Algorithms Arrivals Automation Copper industry Expected values Fittings Methods Neural networks Noise Partitioning Seismic phenomena Standard deviation Time series Underground mines Vibration Wavelet transforms  | 
    
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| Title | Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment Characteristic | 
    
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