Real-time Seismic Amplitude Measurement (RSAM): a volcano monitoring and prediction tool

1991 ◽  
Vol 53 (7) ◽  
pp. 533-545 ◽  
Author(s):  
Elliot T Endo ◽  
Tom Murray
Keyword(s):  
Real Time ◽  
Volcano Monitoring ◽  
Prediction Tool ◽  
Seismic Amplitude ◽  
Amplitude Measurement

scholarly journals Design Of Real-Time Seismic Amplitude Measurement (RSAM) System Using Geophone as the Detection of Seismic Vibration

2019 ◽  
Vol 3 (2) ◽  
pp. 21
Author(s):  
Umi Salamah ◽  
Apik Rusdiarna I.P ◽  
Qonitatul Hidayah ◽  
Aji Nur Rizki
Keyword(s):  
Real Time ◽  
Seismic Vibration ◽  
Seismic Amplitude ◽  
Amplitude Measurement

Indonesia merupakan salah satu negara dengan gunungapi terbanyak di dunia. Rangkaian gunungapi membentang dari Pulau Sumatera, Jawa, Bali dan Nusa Tenggara. Dari kepulauan di Laut Bdana sampai bagian utara Pulau Sulawesi merupakan daerah gunungapi terpanjang di dunia. Indonesia memiliki 129 gunungapi aktif, 70 buah diantaranya berancaman dan 500 buah tidak aktif. Sejak tahun 1800, paling tidak telag tercatat 600 kali letusan oleh 70 gunungapi di Indonesia. Karena itu, Indonesia dapat dikatakan sebagai negara yang rawan bencana, terutama ancaman bencana gunung berapi. Pengamatan, pemantauan, pencatatan, penyebaran informasi dan peringatan tanda bahaya terhadap aktivitas gunungapi menjadi salah satu fokus dalam penanggulangan bencana gunungapi. Untuk mendukung hal tersebut diperlukan instrumentasi deteksi aktivitas vulkanik gunungapi. Salah satu instrumentasi yang digunakan untuk memantau aktivitas gunung berapi Gunung Merapi adalah Real-time Seismic Amplitude Measurement (RSAM). RSAM adalah sistem yang menyediakan pengukuran kontinu dari amplitudo seismik rata-rata absolut dari jumlah stasiun seismik. RSAM menempati peran strategis dalam memantau aktivitas seismik gunung berapi terutama pada saat krisis sebelum letusan. Dalam penelitian ini, perancangan sistem RSAM menggunakan sensor geophone untuk mendeteksi getaran seismik. Frekuensi tes yang diberikan dalam penelitian ini termasuk 10 Hz, 30 Hz, dan 50 Hz. Sistem yang telah dirancang bangun dapat mendeteksi frekuensi dengan baik sebagaimana dibuktikan bahwa semakin besar frekuensi uji maka semakin banyak output grafik yang dihasilkan. Selain itu, besaran yang dihasilkan juga semakin besar. Pada frekuensi 10 Hz, magnitudo yang dihasilkan adalah 0,997, pada 30 Hz magnitudo yang dihasilkan 1,559 sedangkan pada 50 Hz magnitudo yang dihasilkan adalah 1,962. Sistem RSAM yang dirancang bangun menghasilkan amplitudo yang memiliki hubungan linier dengan besarnya getaran sumber disediakan..

Capturing, Preserving, and Digitizing Legacy Seismic Data from the Montserrat Volcano Observatory Analog Seismic Network, July 1995–December 2004

2020 ◽  
Vol 91 (4) ◽  
pp. 2127-2140 ◽  
Author(s):  
Glenn Thompson ◽  
John A. Power ◽  
Jochen Braunmiller ◽  
Andrew B. Lockhart ◽  
Lloyd Lynch ◽  
...  
Keyword(s):  
Real Time ◽  
Seismic Data ◽  
Original Data ◽  
South Florida ◽  
Seismic Network ◽  
Quality Data ◽  
Spectral Amplitude ◽  
Assistance Program ◽  
Waveform Data ◽  
Amplitude Measurement

Abstract An eruption of the Soufrière Hills Volcano (SHV) on the eastern Caribbean island of Montserrat began on 18 July 1995 and continued until February 2010. Within nine days of the eruption onset, an existing four-station analog seismic network (ASN) was expanded to 10 sites. Telemetered data from this network were recorded, processed, and archived locally using a system developed by scientists from the U.S. Geological Survey (USGS) Volcano Disaster Assistance Program (VDAP). In October 1996, a digital seismic network (DSN) was deployed with the ability to capture larger amplitude signals across a broader frequency range. These two networks operated in parallel until December 2004, with separate telemetry and acquisition systems (analysis systems were merged in March 2001). Although the DSN provided better quality data for research, the ASN featured superior real-time monitoring tools and captured valuable data including the only seismic data from the first 15 months of the eruption. These successes of the ASN have been rather overlooked. This article documents the evolution of the ASN, the VDAP system, the original data captured, and the recovery and conversion of more than 230,000 seismic events from legacy SUDS, Hypo71, and Seislog formats into Seisan database with waveform data in miniSEED format. No digital catalog existed for these events, but students at the University of South Florida have classified two-thirds of the 40,000 events that were captured between July 1995 and October 1996. Locations and magnitudes were recovered for ∼10,000 of these events. Real-time seismic amplitude measurement, seismic spectral amplitude measurement, and tiltmeter data were also captured. The result is that the ASN seismic dataset is now more discoverable, accessible, and reusable, in accordance with FAIR data principles. These efforts could catalyze new research on the 1995–2010 SHV eruption. Furthermore, many observatories have data in these same legacy data formats and might benefit from procedures and codes documented here.

On Real-Time Performance Evaluation of Volcano-Monitoring Systems With Wireless Sensor Networks

2015 ◽  
Vol 15 (6) ◽  
pp. 3514-3523 ◽  
Author(s):  
Roman Lara ◽  
Diego Benitez ◽  
Antonio Caamano ◽  
Marco Zennaro ◽  
Jose Luis Rojo-Alvarez
Keyword(s):  
Wireless Sensor Networks ◽  
Performance Evaluation ◽  
Sensor Networks ◽  
Real Time ◽  
Volcano Monitoring ◽  
Wireless Sensor ◽  
Monitoring Systems ◽  
Time Performance

Determining the Main CSMA Parameters for Adequate Performance of WSN for Real-Time Volcano Monitoring System Applications

2017 ◽  
Vol 17 (5) ◽  
pp. 1493-1502 ◽  
Author(s):  
Roman A Lara-Cueva ◽  
Rodolfo Gordillo ◽  
Liliana Valencia ◽  
Diego S. Benitez
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Volcano Monitoring

Method for Real-Time Evaluation of Discharge Rate of Volcanic Ash – Case Study on Intermittent Eruptions at the Sakurajima Volcano, Japan –

2016 ◽  
Vol 11 (1) ◽  
pp. 4-14 ◽  
Author(s):  
Masato Iguchi ◽  
Keyword(s):  
Linear Combination ◽  
Real Time ◽  
Volcanic Ash ◽  
Ground Deformation ◽  
Discharge Rate ◽  
Sakurajima Volcano ◽  
Seismic Amplitude ◽  
Ash Weight ◽  
Better Than

A method for evaluating the volcanic ash discharge rate by using seismic and ground deformation signals is proposed to obtain this rate in real time for southern Kyushu’s Sakurajima volcano. This volcano repeats vulcanian eruptions accompanying significant ground deformation showing deflation and nonvulcanian type eruptions that emit the minor emissions of volcanic ash associated with volcanic tremors but without significant ground deformation. We examined ground deformation and seismic amplitude as they relate to monthly sums of volcanic ash weight ejected from craters. We found that in monthly sums, both deflation ground deformation and the amplitude of volcanic tremors correlate positively with the weight of ejected volcanic ash. A linear combination of terms for ground deformation, seismic amplitude and a correction factor correlates better than single parameter of deflation or seismic amplitude with volcanic ash weight. The linear combination provides the volcanic ash discharge rate in quasi-real time and the total amount of volcanic ash distributed over a wide area immediately after a volcanic eruption ends.

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