Technique of Informative Features Selection in Geoacoustic Emission Signals
Keywords:
geoacoustic emission, geoacoustic pulse model, sparse approximation, informative features, signal patternsAbstract
Studies of geoacoustic emission in a seismically active region in Kamchatka show that geoacoustic signals produce pronounced pulse anomalies during the earthquake preparation and post-seismic relaxation of the local stresses field at the observation point. The qualitative selection of such anomalies is complicated by a strong distortion and weakening of the signal amplitude. A review of existing acoustic emission analysis methods shows that most often researchers turn to the analysis of more accessible to study statistical properties and energy of signals. The distinctive features of the approach proposed by the authors are the extraction of informative features based on the analysis of time and frequency-time structures of geoacoustic signals and the description of various forms of recognizable pulses by a limited pattern set. This study opens up new ideas to develop methods for detecting anomalous behavior of geoacoustic signals, including anomalies before earthquakes.
The paper describes a technique of information extraction from geoacoustic emission pulse streams of sound frequency range. A geoacoustic pulse mathematical model, reflecting the signal generation process from a variety of elementary sources, is presented. A solution to the problem of detection of geoacoustic signal informative features is presented by the means of description of signal fragments by the matrixes of local extrema amplitude ratios and of interval ratios between them. The result of applying the developed algorithm to describe automatically the structure of the detected pulses and to form a pattern set is shown. The patterns characterize the features of geoacoustic emission signals observed at IKIR FEB RAS field stations. A technique of reduction of the detected pulse set dimensions is presented. It allows us to find patterns similar in structure. A solution to the problem of processing of a large data flow by unifying pulses description and their systematization is proposed. A method to identify a geoacoustic emission pulse model using sparse approximation schemes is suggested. An algorithmic solution of the problem of reducing the computational complexity of the matching pursuit method is described. It is to include an iterative refinement algorithm for the solution at each step in the method. The results of the research allowed the authors to create a tool to investigate the dynamic properties of geoacoustic emission signal in order to develop earthquake prediction detectors.
References
2. Saltykov V.A. [On the possibility of using the tidal modulation of seismic waves for forecasting earthquakes]. Fizika Zemli – Physics of the Solid Earth. 2017. vol. 2. pp. 84–96. (In Russ.).
3. Larionov I.A. et al. [Research of the acoustic emission of the near-surface sedimentary rocks in Kamchatka]. Geosistemy perehodnyh zon — Geosystems of Transition Zones. 2017. vol. 3. no. 3. pp. 57–63. (In Russ.).
4. Giovanni G.P. et al. The seismic sequence in Central Italy (August-November 2016) Acoustic Emission (AE) monitoring and analysis. New Concepts in Global Tectonics Journal. 2016. vol. 4. no. 4. pp. 637–663.
5. Kuptsov A.V. [Variations in the geoacoustic emission pattern related to earthquakes on Kamchatka]. Fizika Zemli – Physics of the Solid Earth. 2005. vol. 10. pp. 59–65. (In Russ.).
6. Kuptsov A.V., Larionov I.A., Shevtsov B.M. [Geoacoustic Emission During the Precursory Periods of Kamchatka Earthquakes]. Vulkanologiya i sejsmologiya – Journal of Volcanology and Seismology. 2005. vol. 5. pp. 45–58. (In Russ.).
7. Gordienko V.A. et al. [Anomaly in high-frequency geoacoustic emission as a close earthquake precursor]. Akusticheskij zhurnal – Acoustical physics. 2008. Issue 54. vol. 1. pp. 97–109. (In Russ.).
8. Marapuleс Yu.V., Shcherbina A.O. [Methods for the study of spatial anisotropy of geoacoustic emission]. Elektronnyi zhurnal "Tekhnicheskaia akustika" – Electronic Journal Technical Acoustics. 2008. vol. 14. 17 p. Available at: http://ejta.org/ru/marapuletz (accessed: 11.03.2019). (In Russ.).
9. Perezhogin A.S., Shevtsov B.M. [Models of stress-strain state of rocks during the preparation of earthquakes and their relationship with geo-acoustic observations]. Vychislitel’nye tekhnologii – Computational Technologies. 2009. Issue 14. vol. 3. pp. 48–57. (In Russ.).
10. Biot M.A. Theory of propagation of elastic waves in fluid-saturated porous solid. II. Higher frequency range. The Journal of the Acoustical Society of America. 1956. vol. 28. no. 2. pp. 179–191.
11. Frenkel Ya.I. [On the theory of seismic and seismoelectric phenomena in moist soil]. Izvestiia AN SSSR. Seriia: geografiya i geofizika – Proceedings of the USSR Academy of Sciences. Series: geography and geophysics. 1944. Issue 8. vol. 4. pp. 133–149. (In Russ.).
12. Gassmann F. Elastic waves through a parking of spheres. Geophysics. 1951. vol. 16. no. 4. pp. 673–685.
13. Marapulets Iu.V., Lukovenkova O.O., Tristanov A.B., Kim A.A. Metody registratsii i chastotno-vremennogo analiza signalov geoakusticheskoi emissii [Methods for recording and for time-frequency analysis of geoacoustic emission signals]. Vladivostok: Dalnauka. 2017. 148 p.
14. Shcherbina A.O. On some features of geoacoustic emission signals before earthquakes. E3S Web Conferences. 2017. vol. 20. 6 p. Available at: https://www.e3s-conferences.org/articles/e3sconf/abs/2017/08/e3sconf_strpep2017_03005e3sconf_strpep2017_03005.html (accessed: 12.03.2019).
15. Sychev V.N., Imashev S.A. [Estimation of Hurts exponent of seismic signal]. Geosistemy perehodnyh zon – Geosystems of Transition Zones. 2017. no. 2. pp. 50–61. (In Russ.).
16. Mishchenko M.A. [Statistics of Occurrence of Pre-Seismic Anomalies in Geoacoustic Emission and in Atmospheric Field]. Vestnik KRAUNC. Fiziko-matematicheskie nauki – Bulletin KRASEC. Physical & Mathematical Sciences. 2016. no. 3(14). pp. 47–52. (In Russ.).
17. Senkevich Yu.I., Duke V.A., Mishchenko M.A., Solodchuk A.A. Information approach to the analysis of acoustic and electromagnetic signals. E3S Web of Conferences. 2017. vol. 20. 02012. 9 p.
18. Yang B.Y., Liu R.N., Chen X.F. Sparse Time-Frequency Representation for Incipient Fault Diagnosis of Wind Turbine Drive Train. IEEE Transactions on Instrumentation and Measurement. 2018. vol. 67. no. 11. pp. 2616–2627.
19. Raj S., Ray K.C. Sparse representation of ECG signals for automated recognition of cardiac arrhythmias. Expert systems with applications. 2018. vol. 105. pp. 49–64.
20. Huai S., Zhang S. A novel sparse representation algorithm for AIS real-time signals. EURASIP journal on wireless communications and networking. 2018. vol. 2018. no. 1. pp. 223. Available at: https: //jwcn-eurasipjournals.springeropen.com/articles/10.1186/s13638-018-1244-9 (accessed: 11.03.2019).
21. Mallat S.G., Zhang Z. Matching pursuits with time-frequency dictionaries. IEEE Transactions Signal Processing. 1993. vol. 41. no. 12. pp. 3397–3415.
Senkevich Yu.I. [Structural and linguistic processing of geophysical signals and data series]. Certificate of state registration of computer programs № 2019617637. 18.06.2019. (In Russ.).
Published
How to Cite
Section
Copyright (c) 2019 Юрий Игоревич Сенкевич, Юрий Валентинович Марапулец, Ольга Олеговна Луковенкова, Александра Андреевна Солодчук
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms: Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).