J. A. L. Cruz-Abeyro

Novel ST-MUSIC-based spectral analysis for detection of ULF geomagnetic signals anomalies associated with seismic events in Mexico

Recently, the analysis of ultra-low-frequency (ULF) geomagnetic signals in order to detect seismic anomalies has been reported in several works. Yet, they, although having promising results, present problems for their detection since these anomalies are generally too much weak and embedded in high noise levels. In this work, a short-time multiple signal classification (ST-MUSIC), which is a technique with high-frequency resolution and noise immunity, is proposed for the detection of seismic anomalies in the ULF geomagnetic signals. Besides, the energy (E) of geomagnetic signals processed by ST-MUSIC is also presented as a complementary parameter to measure the fluctuations between seismic activity and seismic calm period. The usefulness and effectiveness of the proposal are demonstrated through the analysis of a synthetic signal and five real signals with earthquakes. The analysed ULF geomagnetic signals have been obtained using a tri-axial fluxgate magnetometer at the Juriquilla station, which is localized in Queretaro, Mexico (geographic coordinates: longitude 100.45° E and latitude 20.70° N). The results obtained show the detection of seismic perturbations before, during, and after the main shock, making the proposal a suitable tool for detecting seismic precursors.

DWT-based methodology for detection of seismic precursors on electric field signals in Mexico

ABSTRACT This paper presents an analysis of atmospheric electric field signals which were taken on an important seismic activity period from 2012 to 2015 to study its relationship with seismic events. For this purpose, several measurements were acquired every second by using a triaxial electric field monitoring system. Furthermore, the discrete wavelet transform (DWT) was applied to electric field signals with seismic events of magnitudes greater than Mw > 5.5, which occurred in Mexico with different focal mechanisms. The analysed epochs consist of 24 h of observations for a data-set corresponding to 55 different earthquakes (EQs). The time series were processed 12 h before and 12 h after each seismic event. The proposed methodology proves to be an efficient tool to detect signals with relations between electric field and seismic activity. The methodology presented herein shows important anomalies on different time instants according to the focal mechanism. Finally, a statistical post-processing algorithm was performed in order to quantify the data dispersion as a measure of seismic activity. It is found that the variance increases before, during, and after the seismic event about the coefficients D1 to D7 obtained using the DWT.

Electromagnetic attenuation of eight earthquakes registered in Mexico using FFT-based spectrum and t-test statistical analysis for ULF Q-R ratios signals

A method to improve the detection of seismo-magnetic signals is presented herein. Eight events registered for periods of 24 hours with seismic activity were analyzed and compared with non-seismic periods of the same duration. The distance between the earthquakes (EQs) and the ultra-low frequency detector is of ρ = (1.8) 100.45M, where M is the magnitude of the EQ reported by the Seismological National Service of Mexico, in a period of three years. An improved fast Fourier transform analysis in the form of the ratio of the vertical magnetic field component to the horizontal one (Q = Bz/Bx) has been developed. There are important differences between the frequencies obtained during the days of seismic activity compared with those with no seismic activity.

Empirical Wavelet Transform-based Detection of Anomalies in ULF Geomagnetic Signals Associated to Seismic Events with a Fuzzy Logic-based System for Automatic Diagnosis

Owing to the relevance and severity of damages caused by earthquakes (EQs), the development and application of new methods for seismic activity detection that offer an efficient and reliable diagnosis in terms of processing and perform‐ ance are still demanding tasks. In this work, the application of the Empirical Wavelet Transform (EWT) for seismic detection in ultra-low-frequency (ULF) geomagnetic signals is presented. For this, several ULF signals associated to seismic activities and random calm periods are analysed. These signals have been obtained through a tri-axial fluxgate magnetometer at the Juriquilla station localized in Queretaro, Mexico, longitude -100.45° N and latitude 20.70°E. In or‐ der to show the advantages of the proposal, a comparison with the discrete wavelet transform (DWT) is presented. The results shown a better detection ca‐ pability of seismic signals before, during, and after the main shock than the ones obtained by the DWT, which makes the proposal a more suitable and relia‐ ble tool for this task. Finally, a fuzzy logic (FL)-based system for automatic di‐ agnosis using the variance of the EWT outputs for the tri-axial fluxgate magnetometer signals is also proposed.