Publications
3rd ECEE & Seismology 2023
SEISMO-ACOUSTIC EVENT DETECTION
Bernd Weber, Péter Mónus, István Bondár, D Rossler, Csenge Czanik, Marcell Pásztor
Using the SeisComp framework with the gempa software packages LAMBDA and KAPPA, we present seismo-acoustic signal analysis of the Russian missile attack near Lviv airport (Ukraine) on March 18, 2022. We processed the records of seismological stations in Poland, Slovakia and Hungary, as well as records of Hungarian and Romanian infrasound arrays using the PMCC analysis in LAMBDA. The resulting pixel families are processed in KAPPA. We demonstrate that LAMBDA detected and located the event and KAPPA distinguished the signal from regular mining explosions and aircrafts. The resulting location is 20 km WSW from the reported impact location near Lviv airport. KAPPA, supporting custom plugins to classify signals, is used to discriminate the missile impact signal from the common detections caused by nearby quarry blasts and aircrafts. The used plugin analyzes several features of the pixel family derived from the PMCC processing within LAMBDA like backazimuth, slowness, duration, frequency range, slope of onset/coda, maximum amplitude, trends in backazimuth and slowness as well as time of detection. The signal analysis showed significant differences to the quarry blast activity, especially in the slope of onset and coda as well as in the signal duration. The recorded aircraft signals showed similar patterns as the missile impact in most features like slope of signal onset/coda and duration, but changes in the backazimuth and slowness over time while the aircraft is passing the infrasound array allowed to discriminate the signals.
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CTBT Science and Technology Conference 2023
Automatic Event Discrimination with Machine Learning Techniques at the Piszkés-tető Infrasound Array, Hungary
Marcell Pásztor https://conferences.ctbto.org/event/23/contributions/4806/
The infrasound array in Hungary at Piszkés-tető (PSZI) has been collecting data since 2017. For signal processing, the Progressive Multichannel Cross-Correlation (PMCC) method is used, which resulted in about a million detections so far. Among these detections there are about 10 000 categorized, hand labelled events from quarry blasts, storms and power plant noise that constitute the dataset for training and testing. We extracted both time and frequency domain features from the raw waveforms, and also calculated PMCC specific features. For event discrimination purposes we tested two machine learning algorithms, the Random Forest and Support Vector Machine methods. These classifiers were trained to separate quarry blasts from storms and coherent noise from the nearby power plant. We measure the performance of the classifiers with the f1 score, and analyse the confusion matrices. For both classifiers the results reach 0.9 f1 score.
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ESC 2021
The crustal structure of the Pannonian Basin and wider region from P-to-S receiver function analysis
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EGU 2022
Bondár, I ; Šindelářová, T ; Ghica, D ; Mitterbauer, U ; Liashchuk, A ; Baše, J ; Chum, J ; Czanik, C ; Ionescu, C ; Neagoe, C et al.
The Central and Eastern European Infrasound Network Bulletin
In: EGU General Assembly 2022, online, 23-27 May 2022
Bécs, Ausztria : European Geosciences Union (EGU) (2022) Paper: EGU22-3503 , 1 p.
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