Abstract

The acquisition of 2–50 Hz low-frequency vibration signals is of great significance for the monitoring researches on engineering seismology, bridges & dams, oil & gas exploration, etc. A multi-cantilever beam low-frequency FBG acceleration sensor is proposed against the low sensitivity that predominates in the low-frequency vibration measurement by FBG acceleration sensors. Structural parameters of the sensor is subjected to simulation analysis and optimization design using the ANSYS software; the real sensor is developed based on the simulation results in the following manner: Three rectangular of the cantilever beams are evenly arranged around the mass block at 120°to improve the sensitivity and alleviate the transverse crosstalk of sensor; in the end, a performance test is performed on the sensor. According to the research findings, the sensor, whose natural frequency is approximately 64 Hz, is applicable for monitoring the low-frequency vibration signals within the range 16–54 Hz. The sensor sensitivity is approximately 87.955pm/ms-2, the linearity being greater than 99%, the transverse interference immunity being lower than 2.58%, and the dynamic range being up to 86 dB. The findings offer a reference for developing sensor of the same type and further improving the sensitivity of fiber optic acceleration sensor.

Details

Title
A multi-cantilever beam low-frequency FBG acceleration sensor
Author
Li, Hong 1 ; Sun, Rui 1 ; Qiu Zhongchao 2 ; Han, Zhiming 1 ; Li, Yanan 1 

 Institute of Disaster Prevention, School of Electronic Science and Control Engineering, Sanhe, China (GRID:grid.470919.2) (ISNI:0000 0004 1789 9593); Key Laboratory of Seismic Dynamics of Hebei Province, Sanhe, China (GRID:grid.470919.2) 
 Institute of Disaster Prevention, School of Electronic Science and Control Engineering, Sanhe, China (GRID:grid.470919.2) (ISNI:0000 0004 1789 9593); Key Laboratory of Seismic Dynamics of Hebei Province, Sanhe, China (GRID:grid.470919.2); Institute of Geophysics, China Earthquake Administration, Beijing, China (GRID:grid.450296.c) (ISNI:0000 0000 9558 2971) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2573134794
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.