Discrimination of doubled acoustic emission events using neural networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985530%3A_____%2F24%3A00597655" target="_blank" >RIV/67985530:_____/24:00597655 - isvavai.cz</a>
Alternative codes found
RIV/67985831:_____/24:00598246 RIV/67985891:_____/24:00597655
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0041624X24002026?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0041624X24002026?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ultras.2024.107439" target="_blank" >10.1016/j.ultras.2024.107439</a>

Result language
angličtina
Original language name
Discrimination of doubled acoustic emission events using neural networks
Original language description
In observatory seismology, the effective automatic processing of seismograms is a time-consuming task. A contemporary approach for seismogram processing is based on the Deep Neural Network formalism, which has been successfully applied in many fields. Here, we present a 4D network, based on U-net architecture, that simultaneously processes seismograms from an entire network. We also interpret Acoustic Emission data based on a laboratory loading experiment. The obtained data was a very good testing set, similar to real seismograms. Our Neural network is designed to detect multiple events. Input data are created by augmentation from previously interpreted single events. The advantage of the approach is that the positions of (multiple) events are exactly known, thus, the efficiency of detection can be evaluated. Even if the method reaches an average efficiency of only around 30% for the onset of individual tracks, average efficiency for the detection of double events was approximately 97% for a maximum target, with a prediction difference of 20 samples. Such is the main benefit of simultaneous network signal processing.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20701 - Environmental and geological engineering, geotechnics

Project
<a href="/en/project/GA22-00580S" target="_blank" >GA22-00580S: The role of rock anisotropy in hydraulic fracturing through acoustic emission</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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