Trudy SPIIRAN
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Informatics and Automation:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Trudy SPIIRAN, 2019, Issue 18, volume 5, Pages 1066–1092
DOI: https://doi.org/10.15622/sp.2019.18.5.1066-1092
(Mi trspy1074)
 

This article is cited in 11 scientific papers (total in 11 papers)

Mathematical Modeling, Numerical Methods

Technique of informative features selection in geoacoustic emission signals

Yu. I. Senkevicha, Yu. V. Marapuletsabc, O. O. Lukovenkovacab, A. A. Solodchuka

a Institute of Cosmophysical Research and Radio Wave Propagation FEB RAS
b KamchatSTU
c KamGU Vitus Bering
Abstract: 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, representing 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 systematisation is proposed. The results of the research allowed the authors to create a tool to investigate the dynamic properties of geoacostic emission signal in order to develop earthquake prediction detectors.
Keywords: geoacoustic emission, geoacoustic pulse model, sparse approximation, informative features, signal patterns.
Funding agency Grant number
Russian Science Foundation 18-11-00087
This research is supported by Russian Science Foundation (project 18-11-00087).
Received: 09.04.2019
Bibliographic databases:
Document Type: Article
UDC: 550.344.094:550.344.094.83:550.348.432
Language: Russian
Citation: Yu. I. Senkevich, Yu. V. Marapulets, O. O. Lukovenkova, A. A. Solodchuk, “Technique of informative features selection in geoacoustic emission signals”, Tr. SPIIRAN, 18:5 (2019), 1066–1092
Citation in format AMSBIB
\Bibitem{SenMarLuk19}
\by Yu.~I.~Senkevich, Yu.~V.~Marapulets, O.~O.~Lukovenkova, A.~A.~Solodchuk
\paper Technique of informative features selection in geoacoustic emission signals
\jour Tr. SPIIRAN
\yr 2019
\vol 18
\issue 5
\pages 1066--1092
\mathnet{http://mi.mathnet.ru/trspy1074}
\crossref{https://doi.org/10.15622/sp.2019.18.5.1066-1092}
\elib{https://elibrary.ru/item.asp?id=40938365}
Linking options:
  • https://www.mathnet.ru/eng/trspy1074
  • https://www.mathnet.ru/eng/trspy/v18/i5/p1066
  • This publication is cited in the following 11 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Informatics and Automation
    Statistics & downloads:
    Abstract page:162
    Full-text PDF :122
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024