scholarly journals Overview of processing and analysis methods for pulse geophysical signals

2020 ◽  
Vol 196 ◽  
pp. 02023
Author(s):  
Olga Lukovenkova ◽  
Yury Senkevich ◽  
Alexandra Solodchuk ◽  
Albert Shcherbina
Keyword(s):  
Matching Pursuit ◽  
Electromagnetic Emission ◽  
Kamchatka Peninsula ◽  
Threshold Scheme ◽  
Structural Description ◽  
Pulse Waveform ◽  
Time Frequency ◽  
Process Dynamics ◽  
Analysis Methods ◽  
Pulse Structure

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.

scholarly journals Analysis of geoacoustic emission and electromagnetic radiation signals accompanying earthquake with magnitude Mw = 7.5

2020 ◽  
Vol 196 ◽  
pp. 03001
Author(s):  
Olga Lukovenkova ◽  
Alexandra Solodchuk
Keyword(s):  
Electromagnetic Radiation ◽  
Frequency Spectrum ◽  
Matching Pursuit ◽  
Kamchatka Peninsula ◽  
Pulse Waveform ◽  
Frequency Spectra ◽  
Pulse Detection ◽  
Geoacoustic Emission ◽  
Matching Pursuit Algorithm ◽  
Electromagnetic Signals

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.

Separating Multiple Moving Sources by Microphone Array Signals for Wayside Acoustic Fault Diagnosis

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Wei Xiong ◽  
Qingbo He ◽  
Zhike Peng
Keyword(s):  
Fault Diagnosis ◽  
Time Domain ◽  
Feature Matching ◽  
Matching Pursuit ◽  
Microphone Array ◽  
Time Frequency ◽  
Moving Sources ◽  
The Time Domain ◽  
Envelope Spectrum ◽  
Threshold Setting

Wayside acoustic defective bearing detector (ADBD) system is a potential technique in ensuring the safety of traveling vehicles. However, Doppler distortion and multiple moving sources aliasing in the acquired acoustic signals decrease the accuracy of defective bearing fault diagnosis. Currently, the method of constructing time-frequency (TF) masks for source separation was limited by an empirical threshold setting. To overcome this limitation, this study proposed a dynamic Doppler multisource separation model and constructed a time domain-separating matrix (TDSM) to realize multiple moving sources separation in the time domain. The TDSM was designed with two steps of (1) constructing separating curves and time domain remapping matrix (TDRM) and (2) remapping each element of separating curves to its corresponding time according to the TDRM. Both TDSM and TDRM were driven by geometrical and motion parameters, which would be estimated by Doppler feature matching pursuit (DFMP) algorithm. After gaining the source components from the observed signals, correlation operation was carried out to estimate source signals. Moreover, fault diagnosis could be carried out by envelope spectrum analysis. Compared with the method of constructing TF masks, the proposed strategy could avoid setting thresholds empirically. Finally, the effectiveness of the proposed technique was validated by simulation and experimental cases. Results indicated the potential of this method for improving the performance of the ADBD system.

scholarly journals RANSAC algorithm for instantaneous frequency estimation and reconstruction of frequency-modulated undersampled signals

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Igor Djurović
Keyword(s):  
Instantaneous Frequency ◽  
Matching Pursuit ◽  
Frequency Estimation ◽  
Consensus Algorithm ◽  
Multidimensional Space ◽  
Instantaneous Frequency Estimation ◽  
Time Frequency ◽  
Polynomial Phase ◽  
Fm Signals ◽  
Fifth Order

AbstractFrequency modulated (FM) signals sampled below the Nyquist rate or with missing samples (nowadays part of wider compressive sensing (CS) framework) are considered. Recently proposed matching pursuit and greedy techniques are inefficient for signals with several phase parameters since they require a search over multidimensional space. An alternative is proposed here based on the random samples consensus algorithm (RANSAC) applied to the instantaneous frequency (IF) estimates obtained from the time-frequency (TF) representation of recordings (undersampled or signal with missing samples). The O’Shea refinement strategy is employed to refine results. The proposed technique is tested against third- and fifth-order polynomial phase signals (PPS) and also for signals corrupted by noise.

scholarly journals The wavelet transforms technique in the computer-aided system for controlling the quarry unmanned vehicles

2021 ◽  
Vol 315 ◽  
pp. 03022
Author(s):  
Ivan Chicherin ◽  
Boris Fedosenkov ◽  
Dmitriy Dubinkin ◽  
Wang Zhenbo
Keyword(s):  
Wavelet Transforms ◽  
Matching Pursuit ◽  
Effective Means ◽  
Unmanned Vehicles ◽  
Open Pit ◽  
Open Pit Mining ◽  
Frequency Distributions ◽  
One Dimensional ◽  
Time Frequency ◽  
Computer Aided

Introduction. Purpose of the work. Within the framework of the computer-aided system, a technology has been formed for the method of controlling the current trajectories (CTs) of unmanned vehicles (UMVs) when they move along routes in a quarry in open pit mining. The purpose of the presented studies is to analyze the application of a wavelet transforms technique to the problem of routing unmanned vehicles when they move along routes within open pit roads. Methodology. The results of modeling certain one-dimensional signals corresponding to the UMV current trajectories when they deviate to the left / right from a nominal axial trajectory (NAT), as well as their time-frequency representations in a wavelet medium are presented. An algorithm of the procedure for displaying scalar UMV CT control signals in a complex medium of time-frequency wavelet transforms has been developed and described. Such a transformation allows for a functionally transparent and information-capacious monitoring of the UMV movement and efficiently manage the processes of trajectory routing dump trucks in an open pit. Research results, analysis. The processes of modifying the UMV movement current trajectories under the control of the computer-aided system are generated using wavelet transforms methods. They are based on algorithms for projecting the trajectory signals with a time-dependent frequency (chirp signals) onto a set of wavelet functions as part of a wavelet thesaurus (wavelet dictionary), executing certain wavelet matching pursuit procedures, and displaying the CT scalar signals in a specific multidimensional medium of Cohen’s class time-frequency distributions. The simulation results in the form of the current trajectory (CT-) signals waveforms and their three-dimensional time-frequency representations as Wigner maps showing the UMV movement in a start-stop mode, as well as the signals of formed continuous deviation trajectories when they leave to the left and to the right from the NAT, are presented. An algorithm for the formation of 3D-representations of UMV current trajectory one-dimensional signals is presented. Conclusion. The conclusion is made that the mathematical technique of wavelet transforms is the most expedient and effective means for computer-aided monitoring and controlling the dynamics of UMV movement along routes within open pit roads.

Application of Joint-Time Frequency Analysis Methods for Nondestructive Evaluation

1999 ◽  
Author(s):  
Ki-Woo Nam ◽  
Kun-Chan Lee ◽  
Jeong-Hwan Oh
Keyword(s):  
Crack Propagation ◽  
Nondestructive Evaluation ◽  
Frequency Analysis ◽  
Cyclic Fatigue ◽  
Frequency Characteristics ◽  
Time Frequency Analysis ◽  
Ultrasonic Signals ◽  
Time Frequency ◽  
Analysis Methods ◽  
Ae Signals

Abstract Application of signal processing techniques to nondestructive evaluation (NDE) in general and acoustic emission (AE) studies in particular has become a standard tool in determining the frequency characteristics of the signals and relating these characteristics to the integrity of the structure under consideration. Recent studies have shown that the frequency characteristics of ultrasonic signals from evolving damage during cyclic (fatigue) and dynamic loads change with time; in other words, the signals are nonstationary, and that these changes can be related to the nature of the damage taking place during loading. A joint time-frequency analysis such as Short Time Fourier Transform (STFT) and Wigner-Ville distribution (WVD), can in principle be used to determine the time dependent frequency characteristics of nonstationary signals in presence of background noise. In this study these techniques are applied to analyze AE signals from fatigue crack propagation in 5083 aluminum alloys and ultrasonic signals in degraded austenitic 316 stainless steels, to study the evolution of damage in these materials. It is demonstrated that the nonstationary characteristics of both AE and ultrasonic signals could be analyzed effectively by these methods. STFT was found to be more effective in analyzing AE signals, and WVD was more effective for analyzing the attenuation and frequency characteristics of degraded materials through ultrasonics. It is indicated that the time-frequency analysis methods should also be useful in evaluating crack propagation and final fracture process resulting from various damages and defects in structural members.

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