Detection of earthquake induced radon precursors by Hilbert Huang Transform

被引:27
作者
Barman, Chiranjib [1 ]
Ghose, Debasis [1 ]
Sinha, Bikash [1 ]
Deb, Argha [2 ]
机构
[1] Ctr Variable Energy Cyclotron, Dept Atom Energy, 1-AF Bidhannagar, Kolkata 700064, India
[2] Jadavpur Univ, Dept Phys, Kolkata 700032, India
关键词
Soil radon-222; Ensemble Empirical Mode Decomposition; Hilbert Huang Transform; Earthquake precursor; Non-stationary; EMPIRICAL MODE DECOMPOSITION; TIME-SERIES; SOIL-GAS; EASTERN-INDIA; PREDICTION; ANOMALIES; FAULT; IDENTIFICATION; GEOCHEMISTRY; FREQUENCY;
D O I
10.1016/j.jappgeo.2016.08.004
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Continuous measurement of radon-222 concentration in soil was carried out across duration of one year at a geologically faulted area having high regional heat flow to detect anomalies caused by seismic activities. The data reveals a range of periodicities present in the radon time series. To identify seismic induced radon changes we treat the time series data through various filtering methods to remove inherent periodicities. The Ensemble Empirical Mode Decomposition (EEMD) is deployed to decompose the signal into its characteristic modes. Hilbert Huang Transform (HHT) is applied for the first time on the physically significant modes obtained by EEMD to represent time-energy-frequency of the recorded soil radon time series. After removing the periodic and quasi-periodic constituents from the original time series, the simulated result shows a forceful correlation in recorded radon-222 anomalies with regional and local seismic events. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:123 / 131
页数:9
相关论文
共 50 条
[11]   Wear detection in gear system using Hilbert-Huang transform [J].
Li, Hui ;
Zhang, Yuping ;
Zheng, Haiqi .
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2006, 20 (11) :1781-1789
[12]   Wear detection in gear system using Hilbert-Huang transform [J].
Hui Li ;
Yuping Zhang ;
Haiqi Zheng .
Journal of Mechanical Science and Technology, 2006, 20 :1781-1789
[13]   Structural damage detection based on improved Hilbert-Huang transform [J].
Ren, Yi-Chun ;
Weng, Pu .
Zhendong yu Chongji/Journal of Vibration and Shock, 2015, 34 (18) :195-199
[14]   Hilbert-Huang Transform and the Application [J].
Liu, Yi ;
An, Hao ;
Bian, Shuangshuang .
PROCEEDINGS OF 2020 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS), 2020, :534-539
[15]   Analysis of Sunspot Variability Using the Hilbert - Huang Transform [J].
Barnhart, Bradley L. ;
Eichinger, William E. .
SOLAR PHYSICS, 2011, 269 (02) :439-449
[16]   WHEEZE DETECTION IN THE RESPIRATORY SOUNDS USING HILBERT-HUANG TRANSFORM [J].
Sayli, Omer .
2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2014, :2194-2197
[17]   Decision thresholding on fMRI activation maps using the Hilbert-Huang transform [J].
Kuo, Po-Chih ;
Liou, Michelle .
JOURNAL OF NEURAL ENGINEERING, 2022, 19 (04)
[18]   Online nonlinear structural damage detection using Hilbert Huang transform and artificial neural networks [J].
Vazirizade, S. M. ;
Bakhshi, A. ;
Bahar, O. .
SCIENTIA IRANICA, 2019, 26 (03) :1266-1279
[19]   Energy-Based Analysis of Mechanisms of Earthquake-Induced Landslide Using Hilbert-Huang Transform and Marginal Spectrum [J].
Fan, Gang ;
Zhang, Li-Min ;
Zhang, Jian-Jing ;
Ouyang, Fang .
ROCK MECHANICS AND ROCK ENGINEERING, 2017, 50 (09) :2425-2441
[20]   Application of Hilbert-Huang Transform and SVM to Coal Gangue Interface Detection [J].
Liu, Wei ;
Yan, Yuhua ;
Wang, Rulin .
JOURNAL OF COMPUTERS, 2011, 6 (06) :1262-1269