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Sound Range AE as a Tool for Diagnostics of Large Technical and Natural Objects
Yuri Marapulets1, Alexandra Solodchuk1, Olga Lukovenkova1
1Laboratory of Acoustic Research, Institute of Cosmophysical Research and Radio Wave Propagation FEB RAS, Kamchatka Region, Elizovskiy District, Mirnaya Str. 7., 684034 Paratunka, Russia.
This study introduces a system for analyzing acoustic emission signals to monitor geological stability and predict earthquakes. It enables precise source localization using multi-component sensors and advanced algorithms for noisy environments.
Area of Science:
- Geophysics
- Seismology
- Acoustics
Background:
- Acoustic emission (AE) in the sound frequency range is crucial for monitoring the stability of geological structures and infrastructure.
- Detecting rock deformation anomalies preceding earthquakes is vital for seismic hazard assessment.
- Existing methods require robust systems for accurate AE source localization and signal analysis.
Purpose of the Study:
- To develop and describe a system for recording, processing, and analyzing acoustic emission signals.
- To enable the determination of the direction to AE sources using a single multi-component sensor.
- To present the application of AE for detecting rock deformation preceding earthquakes.
Main Methods:
- Utilizing multi-component acoustic sensors for AE recording and directivity determination.
- Implementing algorithms for AE pulse detection in noisy backgrounds.
- Applying the Adaptive Matching Pursuit algorithm for AE signal structure analysis.
- Developing a method for AE source direction detection using multi-component sensors.
Main Results:
- A system capable of determining the direction to an AE source with a single multi-component sensor was developed.
- Effective algorithms for AE pulse detection and analysis in noisy conditions were employed.
- The system successfully detected intensified rock deformations associated with earthquake preparation in Kamchatka.
Conclusions:
- Sound range acoustic emission analysis is a viable method for monitoring geological stability.
- The developed system and algorithms enhance the capability to detect precursor signals of seismic events.
- This technology holds promise for improving earthquake preparedness and hazard mitigation strategies.
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