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...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2016/4051701 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832567151236481024 |
|---|---|
| author | Jakub Sokolowski Jakub Obuchowski Radoslaw Zimroz Agnieszka Wylomanska Eugeniusz Koziarz |
| author_facet | Jakub Sokolowski Jakub Obuchowski Radoslaw Zimroz Agnieszka Wylomanska Eugeniusz Koziarz |
| author_sort | Jakub Sokolowski |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1b2655264f6c442eb2b81508e7b1dcb3 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-1b2655264f6c442eb2b81508e7b1dcb32025-02-03T01:02:12ZengWileyShock and Vibration1070-96221875-92032016-01-01201610.1155/2016/40517014051701Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment CharacteristicJakub Sokolowski0Jakub Obuchowski1Radoslaw Zimroz2Agnieszka Wylomanska3Eugeniusz Koziarz4KGHM CUPRUM Ltd., CBR, Sikorskiego 2-8, 53-659 Wrocław, PolandKGHM CUPRUM Ltd., CBR, Sikorskiego 2-8, 53-659 Wrocław, PolandKGHM CUPRUM Ltd., CBR, Sikorskiego 2-8, 53-659 Wrocław, PolandFaculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wroclaw University of Science and Technology, Janiszewskiego 14a, 50-370 Wrocław, PolandKGHM Polska Miedź S.A. O/ZG “Rudna”, Henryka Dąbrowskiego 50, 59-100 Polkowice, PolandThe 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.http://dx.doi.org/10.1155/2016/4051701 |
| spellingShingle | Jakub Sokolowski Jakub Obuchowski Radoslaw Zimroz Agnieszka Wylomanska Eugeniusz Koziarz Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment Characteristic Shock and Vibration |
| title | Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment Characteristic |
| title_full | Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment Characteristic |
| title_fullStr | Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment Characteristic |
| title_full_unstemmed | Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment Characteristic |
| title_short | Algorithm Indicating Moment of P-Wave Arrival Based on Second-Moment Characteristic |
| title_sort | algorithm indicating moment of p wave arrival based on second moment characteristic |
| url | http://dx.doi.org/10.1155/2016/4051701 |
| work_keys_str_mv | AT jakubsokolowski algorithmindicatingmomentofpwavearrivalbasedonsecondmomentcharacteristic AT jakubobuchowski algorithmindicatingmomentofpwavearrivalbasedonsecondmomentcharacteristic AT radoslawzimroz algorithmindicatingmomentofpwavearrivalbasedonsecondmomentcharacteristic AT agnieszkawylomanska algorithmindicatingmomentofpwavearrivalbasedonsecondmomentcharacteristic AT eugeniuszkoziarz algorithmindicatingmomentofpwavearrivalbasedonsecondmomentcharacteristic |