A. A. Fotopoulosb, E. Petrakia, E. M. Vlamakisb, X. A. Argyrioub, N. N. Chatzisavvasb, T. J. Sevvosb, A. Zisosc, C. Nomicosd,
A. Louizie, J. Stonhama, P. H. Yannakopoulosb, D. Nikolopoulosc
a Brunel University, Dept. of Engineering and Design, UK
b Department of Computer Systems Engineering, Technological Educational Institute of Piraeus, Greece
c Department of Physics, Chemistry and Material Science, Technological Educational Institute of Piraeus, Greece d Department of Electronics, Technological Educational
Institution of Athens, Greece e Medical Physics Department, Medical School, University of
Athens, Greece
eRA-7
International
Scientific
Conference
http://env-hum-comp-res.teipir.gr
Address the analogous behavior of the MHz
electromagnetic signals to soil radon
Analysis of both signals with multivariate
statistics, fractal evolving techniques and
Detrended Fluctuation Analysis (DFA)
Radon (222Rn) is a radioactive gas which is present in porous materials, underground and surface waters. It has been used as a trace gas in several studies of Earth, hydro-geology and atmosphere, because of its ability to travel to comparatively long distances and the efficiency of detecting it at very low levels.
Well established criteria have been published for the identification, both of the radon precursors (Cicerone et. al,2009; Ghosh et. al.,2009) and of the precursors of the electromagnetic radiation in the ULF-kHz- MHz range (Eftaxias et. al., 2009; Eftaxias et. al., 2010). According to the earthquake classification of Hayakawa and Hobarra (2010), radon may be considered as a short-term earthquake predictor.
A station for the surveillance of soil radon has been installed in Peloponnese, Ileia Prefecture in South West Greece.
More than 600 Earthquakes of M>4,0 have been occurred in the last Century in Ileia
Radon in soil is monitored by Alpha Guard (AG) Genitron Ltd. via a properly designed unit(Soil Gas Unit, Genitron Ltd.) and accompanying equipment (Genitron, 1997)
Atmospheric pressure (AP), relative humidity (RH) and temperature (T) are continuously monitored as well
EM signals are continuously monitored by a telemetric network which consists of twelve stations (Nomikos and Vallianatos, 1998).
MHz EM radiation is detected by bipolar antennas synchronised in the 41MHz and 46MHz frequencies.
Stations are equipped with novel data-loggers designed adequately for the collection of data of the EM Network (Koulouras et al., 2005).
Fractal evolution of the EM
signals of Vamos station, 41
MHz signal, day 45, year 2008.
i) Time evolution of the
spectral exponent b
(𝑺 (𝒇 )=𝒂⋅𝒇−𝒃)
ii) Spectral exponent log(a) ,
iii) Square of the Spearman's
correlation coefficient
iv) Scalogram of the DWT
respectively.
Spearman correlation coefficient takes
values very close to 1, i.e., the fit to the
power-law is excellent. This is a strong
indicator of the fractal character of the
underlying processes and structures
(Eftaxias et al.,2010).
• Power law beta values in the range
1,5<b<2 indicate anti-persistency and
values above 2 (b>2) persistency
• Switching between persistency and
anti-persistency identifies the long
memory of the system
Vamos Station 46 MHz EM signal days 48-51 year 2008 Neapoli Station 46 MHz EM signal days 75-78 year 2008
High power-law-beta-values presented a very
peculiar increase, as high as 4.
Long-range temporal correlations indicate
strong system memory.
Each value correlates to its long-term history in
fractal manner
Anomalies detected in radon concentrations in 2008 3 & 2
months before 6,5 Earthquake of 6/8/2008
For the power law spectrum 𝑺 (𝒇 )=𝒂⋅𝒇−𝒃 • The area between the two radon
spikes is very critical and presents fractal behaviour (b values above 1,5)
• This low frequency enhancement reveals the predominance of the larger fracture events which is considered as a footprint of the preparation of earthquakes (Eftaxias et al.,2009)
Background noise presents 0<b(t)<1, moving from the the first stage of general disorder to the final stage of general failure presenting stability and self-organisements
Scalogram of the DWT of the 2008 radon signal
Time evolution of the power-law-beta values
Levels of soil radon concentration in 2008
International Scientific Conference eRA-7
Examples of the application of the DWT. (a) Radon 2008 during the five-day
disturbance of the first radon spike (Nikolopoulos et al., 2012). (b) Vamos EM
station, 41 MHz signal, day 45, year 2008. The example corresponds to the
period between the EM bursts which exhibited successive and high values of the
spectral exponent b.
When high frequencies (low negative logarithms) are superimposed on the Power
Spectrum Density, the log-log slope is reduced and, subsequently, the calculated
power-law b-value and the Spearman correlation coefficient.
DFA is a modified root-mean-square analysis of a random walk based on the following concept: a stationary time series with long-range correlations can be integrated.
The measurement of the self-similarity scaling exponent of the integrated series show the long-range correlation properties of the original time series (Peng et al.,1998).
For a given bin size n , the root-mean-square
(rms) fluctuations for this integrated and
detrended signal is calculated:
𝐹 𝑛 =1
𝑁 *𝑦 𝑘 − 𝑛(𝑘)+2𝑁
𝑘=1
Where:
1. i=1,…N a time series of length N
2. k the different time scales
3. y(k) the intergrated signal
4. n the length of each bin
• F(n) is repeated for a broad range of
scales box sizes (n).
• A power-law relation between the
average root-mean square fluctuation
F(n) and the bin size n indicates the
presence of scaling: 𝐹 (𝑛) ∼ 𝑛𝑎 • The scaling exponent α quantifies the
strength of the long-range power-law
correlations in the time series.
Example for the case of the
2008 radon signal. This
figure corresponds to the
period between the two radon
spikes.
The short time scales exhibit
lower slope (α1=1.19), while
the large time scales, higher
(α2=1.55). According to Peng et
al. (1994), these results show
persistent long range power
law correlations.
DFA scatter plot for the
2008 radon time-series.
Exponents a1 and a2
separate radon background
from high power-law-beta
values.
The high power-law-beta
values are characterised by
much larger a1 and a2
DFA scatter plot for the
the EM MHz time-series
of Vamos & Neapoli
Station of EM Telematic
Network.
These DFA values are in
close agreement to the
corresponding values of
the radon background.
Simultaneous appearance of high radon anomalies, high power-law b-values and high power spectral amplitudes, manifests that the wavelet power spectrum can be used as an alternative method for the recognition and visualisation of candidate precursory anomalies in a radon signal.
New MHz EM signals that were derived concurrently to the 2008 radon signal. The signals were analysed with the methods applied to radon. The results indicated analogous behaviour between radon and MHz EM pre-earthquake time-series.
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Eftaxias, K., Balasis, G., Contoyiannis, Y., Papadimitriou, C., Kalimeri, M., Athanasopoulou, L., Nikolopoulos, S., Kopanas, J. , Antonopoulos, G., Nomicos, C., 2009. Unfolding the procedure of characterizing recorded ultra low frequency, kHZ and MHz electromagnetic anomalies prior to the L’Aquila earthquake as pre-seismic ones – Part 1, Nat. Hazard. Earth Sys. 9, 1953–1971.
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