Content-Length: 18259 | pFad | https://doi.org/10.31223/X5XS47

Evaluation of the Grillo sensor, a low-cost accelerometer for IoT-based Real-time seismology
Evaluation of the Grillo sensor, a low-cost accelerometer for IoT-based Real-time seismology

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Authors

Vaclav Matej Kuna, Diego Melgar , Andres Meira

Abstract

Micro-Electro-Mechanical (MEMS) accelerometers are useful for real-time seismology due to their ability to record strong, unsaturated seismic signals. Recent advances in MEMS technologies enable design of instruments with improved capabilities that also allow recording of small signals. As a result, MEMS can be useful across a broad dynamic range and for both major earthquakes and smaller magnitude events. Leveraging improved capabilities from off-the-shelf components, we demonstrate a new, low-cost MEMS-based accelerometer that provides an optimal tradeoff between instrument cost and performance. This article analyzes the instrument's performance in a regional network deployed in southern Mexico over a period of 3+ years for the purpose of earthquake early warning. We discuss the self-noise level, dynamic range, and useful resolution, and compare these parameters to other MEMS-based instruments. Besides the sensor evaluation, we present a large, openly available dataset of strong motion data that comprises continuous ground motion records from 24 instruments since 2017.

DOI

https://doi.org/10.31223/X5XS47

Subjects

Geophysics and Seismology

Keywords

MEMS-based seismometer, Strong-motion seismology

Dates

Published: 2021-01-02 20:08

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
Authors hold equity in Grillo Inc..

Data Availability (Reason not available):
All the data and codes used in this article are openly available.









ApplySandwichStrip

pFad - (p)hone/(F)rame/(a)nonymizer/(d)eclutterfier!      Saves Data!


--- a PPN by Garber Painting Akron. With Image Size Reduction included!

Fetched URL: https://doi.org/10.31223/X5XS47

Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy