地声发射信号信息特征选择技术

Q3 Mathematics SPIIRAS Proceedings Pub Date : 2019-09-19 DOI:10.15622/sp.2019.18.5.1066-1092
Y. Senkevich, Y. Marapulets, O. Lukovenkova, A. Solodchuk
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引用次数: 2

摘要

对堪察加地震活跃区地声发射的研究表明,地声信号在地震准备过程中产生明显的脉冲异常,并在地震后引起观测点局部应力场的松弛。这种异常的定性选择由于信号幅度的强烈失真和减弱而变得复杂。对现有声发射分析方法的回顾表明,研究人员往往转向更容易研究信号的统计性质和能量的分析。该方法的特点是通过分析地声信号的时间和频率-时间结构提取信息特征,并通过有限模式集描述各种形式的可识别脉冲。本研究为开发探测包括地震前异常在内的地声信号异常行为的方法开辟了新的思路。本文介绍了一种从声发射脉冲流中提取信息的方法。提出了一个反映各种基本源信号产生过程的地声脉冲数学模型。提出了用局部极值幅度比矩阵和区间比矩阵描述信号片段的方法,解决了地声信号信息特征的检测问题。最后给出了应用该算法自动描述被测脉冲的结构并形成模式集的结果。这些模式描述了ikiir FEB - RAS野外台站观测到的地声发射信号的特征。提出了一种减小被检测脉冲集尺寸的方法。它能让我们找到结构相似的模式。提出了一种统一脉冲描述及其系统化的方法来解决大数据流处理问题。提出了一种利用稀疏逼近方法识别地声发射脉冲模型的方法。描述了降低匹配追踪方法计算复杂度问题的算法解决方案。它是在方法的每一步都包含一个解的迭代细化算法。研究结果使作者能够创建一个工具来研究地声发射信号的动态特性,从而开发地震预测探测器。
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Technique of Informative Features Selection in Geoacoustic Emission Signals
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.
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来源期刊
SPIIRAS Proceedings
SPIIRAS Proceedings Mathematics-Applied Mathematics
CiteScore
1.90
自引率
0.00%
发文量
0
审稿时长
14 weeks
期刊介绍: The SPIIRAS Proceedings journal publishes scientific, scientific-educational, scientific-popular papers relating to computer science, automation, applied mathematics, interdisciplinary research, as well as information technology, the theoretical foundations of computer science (such as mathematical and related to other scientific disciplines), information security and information protection, decision making and artificial intelligence, mathematical modeling, informatization.
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