Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection Method
To enhance real-time S-wave detection in the railway earthquake early warning (EEW) system, we improved the existing short-term average/long-term average (STA/LTA) algorithm. This enhancement focused on developing a more robust and computationally efficient method. Specifically, we introduced noise...
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MDPI AG
2024-11-01
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| Online Access: | https://www.mdpi.com/1424-8220/24/23/7452 |
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| author | Satoshi Katakami Naoyasu Iwata |
| author_facet | Satoshi Katakami Naoyasu Iwata |
| author_sort | Satoshi Katakami |
| collection | DOAJ |
| description | To enhance real-time S-wave detection in the railway earthquake early warning (EEW) system, we improved the existing short-term average/long-term average (STA/LTA) algorithm. This enhancement focused on developing a more robust and computationally efficient method. Specifically, we introduced noise reflecting P-wave amplitude information before the P-wave to better distinguish between P- and S-waves. By applying this modified STA/LTA method, we achieved a significant improvement in S-wave detection accuracy. For seismic waveforms from stations located within 100 km of the epicenter of each earthquake, with magnitude of M5.5–6.5 and depths ≤ 100 km, the detection accuracy within 1.5 s of the correct time (manual picking) was 81.0%, compared to the 49.0% accuracy of the currently operational railway EEW system. Importantly, despite the improved accuracy, the computational cost of the new method remains comparable to the existing system, allowing for easy integration into the operational EEW system. This development is crucial for preventing false alarms, especially moderate earthquakes (~M6) because issuing warn-ings in unnecessary areas can have a significant social impact. Future plans involve implementing this method into the current system to further improve early warning capabilities and minimize false alarms. |
| format | Article |
| id | doaj-art-7cf2eeb1ca3743cb8d54dba0ca311a20 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-7cf2eeb1ca3743cb8d54dba0ca311a202024-12-13T16:31:34ZengMDPI AGSensors1424-82202024-11-012423745210.3390/s24237452Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection MethodSatoshi Katakami0Naoyasu Iwata1Railway Technical Research Institute, 2-8-38, Hikari-cho, Kokubunji 185-8540, Tokyo, JapanRailway Technical Research Institute, 2-8-38, Hikari-cho, Kokubunji 185-8540, Tokyo, JapanTo enhance real-time S-wave detection in the railway earthquake early warning (EEW) system, we improved the existing short-term average/long-term average (STA/LTA) algorithm. This enhancement focused on developing a more robust and computationally efficient method. Specifically, we introduced noise reflecting P-wave amplitude information before the P-wave to better distinguish between P- and S-waves. By applying this modified STA/LTA method, we achieved a significant improvement in S-wave detection accuracy. For seismic waveforms from stations located within 100 km of the epicenter of each earthquake, with magnitude of M5.5–6.5 and depths ≤ 100 km, the detection accuracy within 1.5 s of the correct time (manual picking) was 81.0%, compared to the 49.0% accuracy of the currently operational railway EEW system. Importantly, despite the improved accuracy, the computational cost of the new method remains comparable to the existing system, allowing for easy integration into the operational EEW system. This development is crucial for preventing false alarms, especially moderate earthquakes (~M6) because issuing warn-ings in unnecessary areas can have a significant social impact. Future plans involve implementing this method into the current system to further improve early warning capabilities and minimize false alarms.https://www.mdpi.com/1424-8220/24/23/7452real-time algorithmearthquake early warningSTA/LTAS-wave pickingK-net |
| spellingShingle | Satoshi Katakami Naoyasu Iwata Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection Method Sensors real-time algorithm earthquake early warning STA/LTA S-wave picking K-net |
| title | Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection Method |
| title_full | Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection Method |
| title_fullStr | Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection Method |
| title_full_unstemmed | Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection Method |
| title_short | Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection Method |
| title_sort | enhancing railway earthquake early warning systems with a low computational cost sta lta based s wave detection method |
| topic | real-time algorithm earthquake early warning STA/LTA S-wave picking K-net |
| url | https://www.mdpi.com/1424-8220/24/23/7452 |
| work_keys_str_mv | AT satoshikatakami enhancingrailwayearthquakeearlywarningsystemswithalowcomputationalcoststaltabasedswavedetectionmethod AT naoyasuiwata enhancingrailwayearthquakeearlywarningsystemswithalowcomputationalcoststaltabasedswavedetectionmethod |