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.