Proceedings ArticleDOI
Detection of P-wave Onset in Seismic Signals using Wavelet Packet Transform
Kanchan Aggarwal,Siddhartha Mukhopadhyay,Arun K. Tangirala +2 more
- pp 1513-1518
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TLDR
This work presents a novel time-frequency based method to efficiently detect and pick the onset of P-wave in seismic signals with low SNR (signal-to-noise ratio), which is superior to the existing methods in accuracy of detection and picking and robustness in the sense of minimal false alarms.Abstract:
Detecting the onset of P-waves in seismic signals is a crucial objective in the development of early warning systems for earthquake-prone regions. This work presents a novel time-frequency based method to efficiently detect and pick the onset of P-wave in seismic signals with low SNR (signal-to-noise ratio). The proposed technique rests on a combination of time-series modelling of seismic noise and wavelet packet transform (WPT), in which the core idea involves tracking the difference between energies of data and one-step ahead model predictions over a select set of wavelet packets (frequency bands). Auto-regressive integrated moving average (ARIMA) models are used for modelling seismic noise, while the packets are selected using the prevailing understanding of P-wave frequency content. The proposed method is superior to the existing methods in two respects, (i) accuracy of detection and picking since it zooms into the frequency bands of interest (corresponding to P-wave onset) and (ii) robustness in the sense of minimal false alarms due to outliers and other sources, especially from low SNR seismograms. The performance of proposed method is illustrated on a simplified simulated process and real-time seismic data sets acquired under low SNR conditions. A comparative study with a recently developed maximum normalized cross correlation method is also presented to demonstrate the superiority of the proposed method.read more
Citations
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Journal ArticleDOI
A Consistently Processed Strong-Motion Database for Chilean Earthquakes
Sebastián Castro,Robert Benavente,Jorge G. F. Crempien,Gabriel Candia,Juan Carlos de la Llera +4 more
TL;DR: In this article , a new strong motion database for researchers and engineers has been provided, which has been processed by traceable and consistent data processing techniques, and all the records are corrected using a four-step novel methodology, which detects the P-wave arrival and introduces a baseline correction based on the reversible-jump Markov chain Monte Carlo method.
Journal ArticleDOI
A prediction framework with time-frequency localization feature for detecting the onset of seismic events.
TL;DR: In this article, the authors proposed a real-time automatic P-wave detector and picker in the prediction framework with a time-frequency localization feature, which brings a diverse set of capabilities in accurately detecting the Pwave onset, especially in low signal-to-noise ratio (SNR) conditions.
Proceedings ArticleDOI
Timely detection of Seismic waves in Ground motion data using Improved S-Transform
TL;DR: In this article, a Linear Gaussian kernel window method is incorporated with S-transform for time frequency decomposition of seismic signals, which progressively controls the window width to increase the concentration of energy and reduce the smearing effect in time-frequency region and minimize the spreading of wave.
References
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Automatic earthquake recognition and timing from single traces
TL;DR: In this article, a computer program was developed for the automatic detection and timing of earthquakes on a single seismic trace, which operates on line and is sufficiently simple that it is expected to work in inexpensive low-power microprocessors in field applications.
Journal ArticleDOI
A comparison of select trigger algorithms for automated global seismic phase and event detection
Mitchell M. Withers,Richard C. Aster,Christopher John Young,J.I. Beiriger,Mark Harris,S.G. Moore,Julian Trujillo +6 more
TL;DR: While no algorithm was clearly optimal under all source, receiver, path, and noise conditions tested, an STA/LTA algorithm incorporating adaptive window lengths controlled by nonstationary seismogram spectral characteristics was found to provide an output that best met the requirements of a global correlated event-detection and location system.
Journal ArticleDOI
Robust automatic P-phase picking: an on-line implementation in the analysis of broadband seismogram recordings
Reinoud Sleeman,Torild van Eck +1 more
TL;DR: The AR-AIC picker has been tested successfully and implemented on the Z-component of the broadband station HGN to provide automatic P-phase picks for a rapid warning system and is shown to provide accurate and robust automatic picks on a large experimental database.
Journal ArticleDOI
PAI-S/K: A robust automatic seismic P phase arrival identification scheme
TL;DR: A new approach based on higher-order statistics (HOS) is introduced that overcomes the subjectivity of human intervention and eliminates the noise factor, making the proposed PAI-S/K scheme an attractive candidate for huge seismic data assessment in a real-time context.