The use of the empirical mode decomposition method to clean and restavration acoustic emission signal

The results of the study of the possibility of using the empirical mode decomposition method for cleaning geoacoustic emission signals from various types of noise are presented. It is shown that the application of the method allows to increase the ratio of the signal noise 3-6 dB depending on the ratio of signal dispersion and noise in the input signal. The examples demonstrate the ability to remove trends and harmonic interference, as well as the ability to highlight a useful signal when masking its powerful noise. A comparative evaluation of the method in relation to the low-frequency filtration is carried out. The limitation of the method applicability in the case of processing of pulse signals asymmetric with respect to its average value is indicated

Search for anomalies in pulse flows of acoustic and electromagnetic emissions

Timely warning of disasters caused by earthquakes ensures life safety. Therefore, the search for markers of pre-seismic events preceding earthquakes remains an important research task. The article presents experimental methods for assessing seismic activity in the Kamchatka region based on the results of processing and analysis of geoacoustic and electromagnetic emission signals. The research is aimed at detecting anomalies in quantitative and qualitative indicators that characterize the pulse streams of acoustic emission of near-surface rocks and electromagnetic emission in the surface layer of the atmosphere. Signal processing and analysis are carried out using special algorithms that take into account the structural features of the variety of pulse shapes and their distribution over time

Auto clustering of the variety of pulse signals based on their symbolic description

In a number of applied studies of geophysics, medicine, cosmophysics, atomic physics and other fields of knowledge, useful information is often hidden in the character of the behavior of a stream of frequency modulated pulses, which are represented by a large variety of forms, significantly different from each other up to several orders value of magnitude amplitude and durations. Noise is often present in the signal. Under these conditions, the problem arises of identifying both individual pulses and groups of pulses to assess the connection between their dynamic characteristics and the state of system. To solve the problem by a method is proposed that includes signal cleaning from interference, the operation of extracting and converting pulses into a code representing a sequence of invariant amplitude and time transformations of similar pulses combined by a single graphic pattern called “symbol”. All symbols extracted from the signal make up the alphabet. A procedure for narrowing the dimension of the alphabet is shown, which allows you to automatically divide it into clusters according to the degree of coincidence of the code. The results of the practical application of the developed method for the selection of base classes of the geoacoustic emission (GAS) signals related to the objective data of the state of the signal-generating medium are presented. The study used data from the archives of observations IKIR FEB RAS

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