Joint Perturbation in Geoacoustic Emission, Radon, Thoron, and Atmospheric Electric Field Based on Observations in Kamchatka

Rulenko, O. P.; Marapulets, Yu. V.; Kuzmin, Yu. D.; Solodchuk, Alexandra

doi:10.1134/s1069351319050094

Cited by 12 publications

(3 citation statements)

References 27 publications

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“…St-Laurent et al and Freund et al comprehensively described the direct relationship between the electrical anomaly generated during the seismogenic process in the solid earth before the earthquake and the positively charged "holes" generated along with the compression process in igneous rocks during the seismogenic process [51,52]. Another explanation is that a radon anomaly before earthquakes is considered one of the main physical mechanisms of electromagnetic precursor phenomena [53,54]. A plethora of research findings have consistently demonstrated that significant changes occur in the crustal structure near the epicenter prior to major earthquakes.…”

Section: Discussionmentioning

confidence: 99%

Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021

Nie,

Zhang

2023

Atmosphere

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This study reports the atmospheric electric field (AEF) anomalies associated with seismic-geological activity recorded by the monitoring network in the Sichuan–Yunnan region of China during the 15–30 days prior to the Yangbi earthquake in Yunnan Province, China, on 21 May 2021. Based on the real-time AEF data from continuous observation, this study summarized the characteristics of the anomalous interference of different meteorological factors on the AEF, compared the simultaneous meteorological data of the AEF anomalies, and ruled out the influence of precipitation, wind, fog, and other weather factors on the AEF anomalies in Yangbi County prior to the Yangbi Ms 6.4 earthquake. The AEF anomalies were identified and extracted from the two-month data from 1 April to 1 June, which were from multiple days, stations, and rupture zones near the 100 km radius from the epicenter of the Yangbi Ms 6.4 main earthquake. Using time series and wavelet transform analysis methods, the obvious common features of the anomalies were summarized, and the homology of the anomalies was verified. The main outcome of the investigation in this study will be used to distinguish and characterize the AEF anomalies associated with pre-seismic geologic activity of non-meteorological elements in the near future.

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Section: Discussionmentioning

confidence: 99%

Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021

Nie,

Zhang

2023

Atmosphere

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“…It was shown in [1,2] that AE intensity increases at the frequency of 25 kHz 2-3 days before strong earthquakes. According to [19,20], anomalies in the form of signal level increase appear in the frequency range of more than 6.5 kHz in the AE signals accumulated by 1 s. The results of time-frequency analysis of single AE pulses registered 1-7 days before earthquakes are presented in [21,22]. According to these results, the number of pulses of a certain frequency increases before strong earthquakes.…”

Section: Examples Of Identification Of Pre-seismic Ae Anomaliesmentioning

confidence: 99%

Method of Analysis and Classification of Acoustic Emission Signals to Identify Pre-Seismic Anomalies

Marapulets¹,

Senkevich²,

Lukovenkova³

et al. 2020

Adv. sci. technol. eng. syst. j.

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“…Continuous monitoring of geophysical signals at various stages of the deformation process has been carried out for more than 20 years at the IKIR FEB RAS geodynamic polygon in the seismically active region (Kamchatka Peninsula). The dynamics of pulse flow parameters of the recorded geophysical signals can be considered as an indicator of the stress-strain state of the geophysical system that generates these signals [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Overview of processing and analysis methods for pulse geophysical signals

et al. 2020

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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.

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Joint Perturbation in Geoacoustic Emission, Radon, Thoron, and Atmospheric Electric Field Based on Observations in Kamchatka

Cited by 12 publications

References 27 publications

Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021

Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021

Method of Analysis and Classification of Acoustic Emission Signals to Identify Pre-Seismic Anomalies

Overview of processing and analysis methods for pulse geophysical signals

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