scholarly journals Performance Evaluation of Low-Cost Seismic Sensors for Dense Earthquake Early Warning: 2018–2019 Field Testing in Southwest China

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1999 ◽  
Author(s):  
Jihua Fu ◽  
Zhitao Li ◽  
Hao Meng ◽  
Jianjun Wang ◽  
Xinjian Shan
Keyword(s):  
Early Warning ◽  
Dynamic Range ◽  
Low Cost ◽  
Noise Analysis ◽  
Field Testing ◽  
Earthquake Early Warning ◽  
Real Field ◽  
Seismic Sensors ◽  
Good Consistency ◽  
Class C

Earthquake Early Warning (EEW) was proved to be a potential means of disaster reduction. Unfortunately, the performance of the EEW system is largely determined by the density of EEW network. How to reduce the cost of sensors has become an urgent problem for building a dense EEW. A low-cost seismic sensor integrated with a Class C MEMS accelerometer was proposed in this paper. Based on minimal structure design, the sensor’s reliability was enhanced, while the costs were cut down as well. To fully reveal the performance, ten of the seismic sensors were installed and tested in Sichuan Province, southwest of China from May 2018 to February 2019. The seismic records obtained by the MNSMSs were compared with those by the traditional strong motion seismographs. The records obtained by the MNSMSs have good consistency with the data obtained by the Etnas. The MNSMSs can obtain clear seismic phases that are enough to trigger earthquake detections for EEW. By noise analysis, different channels of the same sensor and different sensors have good consistency. The tested dynamic range (over 87 dB) and useful resolution (over 14.5 bits) are completely in conformity with the designed parameters. Through real field testing, small earthquakes (M 3.1–3.6) can be detected by all three components E-W, N-S, and U-D within 50 km. In all, the low-cost seismic sensor proposed as a high-performance Class C MEMS sensor can meet the needs of dense EEW in terms of noise, dynamic range, useful resolution, reliability, and detecting capabilities.

scholarly journals Performance Evaluation of a Dense MEMS-Based Seismic Sensor Array Deployed in the Sichuan-Yunnan Border Region for Earthquake Early Warning

Micromachines ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 735 ◽  
Author(s):  
Chaoyong Peng ◽  
Peng Jiang ◽  
Quansheng Chen ◽  
Qiang Ma ◽  
Jiansi Yang
Keyword(s):  
Early Warning ◽  
High Performance ◽  
Dynamic Range ◽  
Low Cost ◽  
Seismic Intensity ◽  
Earthquake Early Warning ◽  
Border Region ◽  
Disaster Mitigation ◽  
Ground Acceleration ◽  
Percentage Difference

With the last decades of development, earthquake early warning (EEW) has proven to be one of the potential means for disaster mitigation. Usually, the density of the EEW network determines the performance of the EEW system. For reducing the cost of sensors and building a dense EEW network, an upgraded low-cost Micro Electro Mechanical System (MEMS)-based sensor named GL-P2B was developed in this research. This device uses a new high-performance CPU board and is built on a custom-tailored Linux 3.6.9 operating system integrating with seismological processing. Approximately 170 GL-P2Bs were installed and tested in the Sichuan-Yunnan border region from January 2017 to December 2018. We evaluated its performance on noise-level, dynamic range (DR), useful resolution (NU), collocated recording comparison, and shake map generation. The results proved that GL-P2B can be classified as a type of Class-B sensor. The records obtained are consistent with the data obtained by the collocated traditional force-balanced accelerometers even for stations with an epicenter distance of more than 150 km, and most of the relative percentage difference of peak ground acceleration (PGA) values is smaller than 10%. In addition, with the current density of the GL-P2B seismic network, near-real-time refined shake maps without using values derived for virtual stations could be directly generated, which will significantly improve the capability for earthquake emergency response. Overall, this MEMS-based sensor can meet the requirements of dense EEW purpose and lower the total investment of the National System for Fast Seismic Intensity Report and Earthquake Early Warning project.

Distributed Sensor System for Earthquake Early Warning Based on the Massive Use of Low Cost Accelerometers

2015 ◽  
Vol 13 (1) ◽  
pp. 291-298 ◽  
Author(s):  
Ana Maria Zambrano Vizuete ◽  
Israel Perez Llopis ◽  
Carlos Palau ◽  
Manuel Esteve Domingo
Keyword(s):  
Early Warning ◽  
Low Cost ◽  
Earthquake Early Warning ◽  
Sensor System ◽  
Distributed Sensor

Performance of a Low‐Cost Earthquake Early Warning System (P‐Alert) during the 2016ML 6.4 Meinong (Taiwan) Earthquake

2016 ◽  
Vol 87 (5) ◽  
pp. 1050-1059 ◽  
Author(s):  
Yih‐Min Wu ◽  
Wen‐Tzong Liang ◽  
Himanshu Mittal ◽  
Wei‐An Chao ◽  
Cheng‐Horng Lin ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Low Cost ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Earthquake Early Warning System ◽  
System P ◽  
Taiwan Earthquake

Application of Waveform Stacking to Low-Cost Local Earthquake Early Warning Arrays in Taiwan

2015 ◽  
Vol 86 (6) ◽  
pp. 1668-1673
Author(s):  
Cheng-Yung Tasi ◽  
Ting-Li Lin ◽  
Yih-Min Wu
Keyword(s):  
Early Warning ◽  
Low Cost ◽  
Earthquake Early Warning ◽  
Local Earthquake

scholarly journals A High-Density Seismic Network for Earthquake Early Warning in Taiwan Based on Low Cost Sensors

2013 ◽  
Vol 84 (6) ◽  
pp. 1048-1054 ◽  
Author(s):  
Y.-M. Wu ◽  
D.-Y. Chen ◽  
T.-L. Lin ◽  
C.-Y. Hsieh ◽  
T.-L. Chin ◽  
...  
Keyword(s):  
Early Warning ◽  
Low Cost ◽  
High Density ◽  
Seismic Network ◽  
Earthquake Early Warning

MEMS Accelerometer Mini-Array (MAMA): A Low-Cost Implementation for Earthquake Early Warning Enhancement

2019 ◽  
Vol 35 (1) ◽  
pp. 21-38 ◽  
Author(s):  
Ran N. Nof ◽  
Angela I. Chung ◽  
Horst Rademacher ◽  
Lori Dengler ◽  
Richard M. Allen
Keyword(s):  
Early Warning ◽  
Microelectromechanical Systems ◽  
Low Cost ◽  
Early Warning Systems ◽  
Earthquake Early Warning ◽  
Mems Accelerometer ◽  
Minimum Number ◽  
Back Azimuth ◽  
Time Required ◽  
Prohibitive Cost

Earthquake Early Warning Systems (EEWS) are often challenged when the earthquakes occur outside the seismic network or where the station density is sparse. In these situations, poor locations and large alert delays are more common because of the limited azimuthal coverage and the time required for the wavefield to reach the minimum number of seismic stations to issue an alert. Seismic arrays can be used to derive the directivity of the wavefield and obtain better location. However, they are uncommon because of the prohibitive cost of the sensors. Here, we propose the development of an array-based approach using mini-arrays of low-cost Microelectromechanical Systems (MEMS) accelerometers and show how they can be used to improve EEWS. In this paper, we demonstrate this approach using data from two MEMS Accelerometer Mini-Arrays (MAMA) deployed at University of California Berkeley and Humboldt State University. We use a new low-cost ( <U.S. $150) Data Acquisition Unit and solve for the back azimuth of seven events with magnitudes ranging from Mw 2.7 to 5.1 at distances of 5 km to 106 km.

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