Методика выделения информативных признаков в сигналах геоакустической эмиссии

Исследования геоакустической эмиссии в сейсмоактивном регионе на Камчатке показывают, что при подготовке землетрясений и последующей релаксации поля локальных напряжений в пункте наблюдений в геоакустических сигналах возникают ярко выраженные импульсные аномалии. Качественному выделению таких аномалий препятствуют сильное искажение и ослабление амплитуды сигнала. Обзор существующих методов анализа акустической эмиссии показывает, что чаще всего исследователи обращаются к анализу энергетических и статистических свойств сигналов, как более доступных для изучения. Отличительными особенностями предлагаемого авторами подхода являются выделение информативных признаков на основе анализа временной и частотно-временной структур геоакустических сигналов и описание многообразных форм распознаваемых импульсов ограниченным набором паттернов. Настоящее исследование открывает перспективу разработки новых методов выявления аномального поведения геоакустических сигналов, в том числе и перед землетрясениями. В работе описана методика извлечения информации из потоков импульсов геоакустической эмиссии звукового частотного диапазона. Представлена математическая модель геоакустического импульса, отражающая процесс генерации сигнала от множества элементарных источников. Приводится решение задачи выделения информативных признаков в геоакустических сигналах путем описания фрагментов сигнала матрицами отношений амплитуд локальных экстремумов и интервалов между ними. Приводится результат применения разработанного алгоритма для автоматического описания структуры выделяемых импульсов и для образования множества паттернов, характеризующих особенности сигналов геоакустической эмиссии, наблюдаемых на полевых станциях ИКИР ДВО РАН. Представлена методика сокращения размерности множества выделенных импульсов, позволяющая найти близкие по структуре паттерны. Предложено решение проблемы обработки большого потока данных путем унификации описания импульсов и их систематизации. Предлагается метод идентификации модели геоакустического импульса с использованием разреженных аппроксимационных схем. Дано алгоритмическое решение задачи понижения вычислительной сложности метода согласованного преследования, заключающееся во включении в метод алгоритма итерационного уточнения решения на каждом шаге. Результаты проведенных научных работ позволили создать инструмент для исследования динамических свойств сигналов геоакустической эмиссии в интересах разработки детекторов предсказания землетрясений

Application of adaptive wavelet thresholding to recovery geoacoustic signal pulse waveforms

Recorded geoacoustic signals often contain noise and interference. Their appearance is caused by various reasons, e.g. of propagation environment heterogeneity, weather condition influence, human activity, etc. So, geoacoustic emission signals contain a persistent background noise that changes in intensity over time. This noise significantly distorts the geoacoustic pulse waveforms and thus complicates analysis of the signal characteristics. The article presents results of estimating the geoacoustic signal background noise. On the basis of these estimates, a method of adaptive wavelet thresholding is proposed to remove noise from the signal and recovery the single pulse waveforms. In conclusion, the results of a computational experiment are presented. They confirm effectiveness of using the chosen method for the geoacoustic signal preprocessing. The work was carried out as part of the implementation of the state task AAAA-A21-121011290003-0

Analysis of geoacoustic emission and electromagnetic radiation signals accompanying earthquake with magnitude

The paper is devoted to the analysis of frequency spectra and pulse waveform variety of the geoacoustic and electromagnetic signals recorded on Kamchatka Peninsula at “Karymshina” site during seismically calm and active periods. Signal pre-processing includes pulse detection and their waveforms reconstruction. A frequency spectrum is analyzed using the Adaptive Matching Pursuit algorithm. To study a variety of waveforms, each pulse is encoded by a special descriptive matrix. Then pulse classification based on similarity of the descriptive matrices is performed. Thus, a signal alphabet is formed. The authors analyzed the geophysical signals recorded before, during and after the earthquake with the magnitude Mw = 7.5 dated March 25, 2020. The obtained estimates of frequency spectra and signal alphabets are compared with the analysis results of signal recoded during the seismically calm period of March 22, 2020

Adaptive Approach to Time-Frequency Analysis of AE Signals of Rocks

The paper describes a new adaptive approach to the investigation of acoustic emission of rocks, the anomalies of which may serve as short-term precursors of strong earthquakes. The basis of the approach is complex methods for monitoring acoustic emission and for analysis of its time-frequency content. Piezoceramic hydrophones and vector receivers, installed at the bottom of natural and artificial water bodies, as well as in boreholes with water, are used as acoustic emission sensors. To perform a time-frequency analysis of geoacoustic signals, we use a sparse approximation based on the developed Adaptive Matching Pursuit algorithm. The application of this algorithm in the analysis makes it possible to adapt to the concrete characteristics of each geoacoustic pulse. Results of the application of the developed approach for the investigation of acoustic emission anomalies, occurring before earthquakes, are presented. We analyzed the earthquakes, that occurred from 2011 to 2016 in the seismically active region of the Kamchatka peninsula, which is a part of the circum-Pacific orogenic belt also known as the “Ring of Fire”. It was discovered that geoacoustic pulse frequency content changes before a seismic event and returns to the initial state after an earthquake. That allows us to make a conclusion on the transformation of acoustic emission source scales before earthquakes. The obtained results may be useful for the development of the systems for environmental monitoring and detection of earthquake occurrences

Parallel adaptive sparse approximation methods for analysis of geoacoustic pulses

The article is devoted to a new approach in the analysis of geoacoustic pulses. The authors proposed a mathematical model based on a sparse representation of the signal. An adaptive matching pursuit method has been developed to identify model parameters. A parallel implementation of this algorithm is proposed on the CUDA platform. This allows real-time processing and modeling of signals

Overview of processing and analysis methods for pulse geophysical signals

The paper discusses the processing and analysis methods for the geoacoustic and electromagnetic emission pulse signals recorded for more than 20 years at the IKIR FEB RAS geodynamic proving ground (Kamchatka Peninsula). The methods for pulse detection, waveform reconstruction, pulse time-frequency analysis using adaptive sparse approximation, structural description of pulse waveforms and pulse classification are proposed. To detect pulses, the adaptive threshold scheme is used. It adjusts to the noise level of a processed signal. To analyze time-frequency structure of the pulses, the adaptive matching pursuit algorithm is used. To identify pulse waveform, the structural description method is proposed. It encodes pulses with special image matrices. The method of the identified pulses classification is considered. Since the methods for pulse structure analysis are sensitive to noise and distortions, the authors propose the method for pulse waveform reconstruction based on wavelet filtering. The geophysical signal information features determined during the analysis can be used to search for anomalies in the data, and then establish a relationship between these anomalies and deformation process dynamics, in particular, with earthquake development processes

Parallel adaptive sparse approximation methods for analysis of geoacoustic pulses

The article is devoted to a new approach in the analysis of geoacoustic pulses. The authors proposed a mathematical model based on a sparse representation of the signal. An adaptive matching pursuit method has been developed to identify model parameters. A parallel implementation of this algorithm is proposed on the CUDA platform. This allows real-time processing and modeling of signals

Complex analysis of pre-seismic geoacoustic and electromagnetic emission signals

The article describes the results of complex analysis of pre-seismic signals of electromagnetic and geoacoustic radiation. We analyzed the frequency content of single sferics and geoacoustic impulses recorded before the Zhupanov earthquake that occurred on January 30, 2016. The signals were analyzed using sparse approximation method, in particular Adaptive Matched Pursuit. Background signals were studied together with pre-seismic ones. Distributions of frequencies, that are part of background and pre-seismic signals, were compared. Differences in the frequency content of pre-seismic sferics and geoacoustic impulses were found. The revealed features of pre-seismic signals in the future can be used in the design of systems for monitoring, forecasting and prevention of natural disasters. The research was supported by Russian Science Foundation (project No. 18-11-00087)

Sound Range AE as a Tool for Diagnostics of Large Technical and Natural Objects

Application of acoustic emission of the sound frequency range is under consideration. This range is of current interest for the diagnostics of the stability of mountain slopes, glaciers, ice covers, large technical constructions (bridges, dams, etc.) as well as for the detection of rock deformation anomalies preceding earthquakes. Acoustic sensors, which can be used to record and to determine the directivity of acoustic emission of the sound frequency range, are under consideration. The structure of the system for acoustic emission recording, processing and analysis is described. This system makes it possible to determine the direction to the acoustic emission source using one multi-component sensor. We also consider the algorithms for detection of acoustic emission pulses in a noisy background, and for the analysis of their structure using the Adaptive Matching Pursuit algorithm. A method for the detection of the direction to an acoustic emission signal source based on multi-component sensors is described. The results of application of sound range acoustic emission for the detection of the intensification of rock deformations, associated with earthquake preparation and development in the seismically active region of Kamchatka peninsula, are presented