Smart Sensor Efficient Signal Processing for Earthquake Early Detection

This paper presents a new method for earthquake early warning alert that uses a smart sampling technique that expose the signal information in a way that it is simpler to infer knowledge. The objective is to estimate, from the first few seconds of the P wave, if the incoming earthquake is destructive or not. The proposed method is described and compared to conventional approaches. Performance results for real seismic data are shown highlighting the results for earthquakes of different magnitudes. Preliminary results are excellent for inferring damage based on the approach of a single seismic station.

[1]  A. Pietrosanto,et al.  Normalizing transducer signals: An overview of a proposed standard , 2014, 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings.

[2]  D. Bindi,et al.  On-site earthquake early warning: a partially non-ergodic perspective from the site effects point of view , 2018, Geophysical Journal International.

[3]  A. Pietrosanto,et al.  Period measurement with an ARM microcontroller , 2015, 2015 XVIII AISEM Annual Conference.

[4]  Hiroo Kanamori,et al.  Real-Time Seismology and Earthquake Damage Mitigation , 2005 .

[5]  Antonio Pietrosanto,et al.  A comparison between FFT and MCT for period measurement with an ARM microcontroller , 2015, 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings.

[6]  Christopher John Young,et al.  A comparison of select trigger algorithms for automated global seismic phase and event detection , 1998, Bulletin of the Seismological Society of America.

[7]  Vincenzo Paciello,et al.  IEEE 21451-001 Signal Treatment Applied to Smart Transducers , 2018, Sensors.

[8]  Vincenzo Paciello,et al.  A Comparison Between Sensor Signal Preprocessing Techniques , 2015, IEEE Sensors Journal.

[9]  Sven Treitel,et al.  Geophysical Signal Analysis , 2000 .

[10]  Jiun Ting Ding,et al.  Developing an energy-efficient and low-delay wake-up wireless sensor network-based structural health monitoring system using on-site earthquake early warning system and wake-on radio , 2019 .

[11]  Richard M. Allen,et al.  The Status of Earthquake Early Warning around the World: An Introductory Overview , 2009 .

[12]  Suprijanto,et al.  Detection of P-wave on broadband seismometer using discrete wavelet denoising , 2013, 2013 3rd International Conference on Instrumentation Control and Automation (ICA).

[13]  Emmanouil Z. Psarakis,et al.  Automatic Seismic Signal Detection via Record Segmentation , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Koji Inoue,et al.  Automatic Arrival Time Detection for Earthquakes Based on Stacked Denoising Autoencoder , 2018, IEEE Geoscience and Remote Sensing Letters.

[15]  Ahmed Shalaby,et al.  Automatic arrival time detection for earthquakes based on logarithmic transformation , 2017, 2017 29th International Conference on Microelectronics (ICM).

[16]  R. Madariaga,et al.  P‐Wave Attenuation with Implications for Earthquake Early Warning , 2016 .

[17]  Initial 30 seconds of the 2011 off the Pacific coast of Tohoku Earthquake (Mw 9.0)—amplitude and τc for magnitude estimation for Earthquake Early Warning— , 2011 .

[18]  Shunroku Yamamoto,et al.  On the estimation of seismic intensity in earthquake early warning systems , 2008 .

[19]  Hiroo Kanamori,et al.  Earthquake early warning: Concepts, methods and physical grounds , 2011 .

[20]  Vincenzo Paciello,et al.  ISO/IEC/IEEE 21451 Smart Sensor Network for the Evaluation of Motorcycle Suspension Systems , 2015, IEEE Sensors Journal.

[21]  R. Allen,et al.  Application of Seismic Array Processing to Earthquake Early Warning , 2013 .