Z.X Yang
Dynamic characterization method of accelerometers based on the Hopkinson bar calibration system
Yang, Z.X; Wang, Q.; Du, H.M.; Fan, J.B; Liang, J.
Abstract
The dynamic characterization of accelerometers is the prerequisite and insurance for highly accurate measurement of dynamic acceleration signals. The main problem of dynamic characterization is the lack of effective methods to deal with model coefficients and the order coupling effect, which could severely influence the identification accuracy. This paper presents a novel approach to solve the identification coupling problem through synchronous iteration and compensation. In order to guarantee the precision of the dynamic model, the Hopkinson bar dynamic calibration system with a traceable excitation acceleration signal is proposed. The feasibility of dynamic modelling is proved by the data comparison of experiment result and model regression result in the time domain. Based on the dynamic model, a dynamic compensation model is established, which improves the dynamic performance by frequency coverage extension. Finally, the results of the dynamic modelling and dynamic compensation are demonstrated by means of the calibration experiment in the paper.
Citation
Yang, Z., Wang, Q., Du, H., Fan, J., & Liang, J. (2019). Dynamic characterization method of accelerometers based on the Hopkinson bar calibration system. Sensors and Actuators A: Physical, 293, 21-28. https://doi.org/10.1016/j.sna.2019.03.035
| Journal Article Type | Article |
|---|---|
| Acceptance Date | Mar 22, 2019 |
| Online Publication Date | Apr 15, 2019 |
| Publication Date | Jul 31, 2019 |
| Deposit Date | Mar 26, 2019 |
| Publicly Available Date | Jan 3, 2024 |
| Journal | Sensors and Actuators A: Physical |
| Print ISSN | 0924-4247 |
| Publisher | Elsevier |
| Peer Reviewed | Peer Reviewed |
| Volume | 293 |
| Pages | 21-28 |
| DOI | https://doi.org/10.1016/j.sna.2019.03.035 |
| Public URL | https://durham-repository.worktribe.com/output/1300158 |
Files
Accepted Journal Article
(1.2 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by-nc-nd/4.0/
Copyright Statement
© 2019 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
Air-Gapped Current Transformer simulation and accuracy assessment
(2022)
Conference Proceeding
Structure health monitoring of concrete structures using magnetic flux leakage
(2022)
Conference Proceeding
A comparison of air pollution in developed and developing cities: A case study of London and Beijing
(2022)
Conference Proceeding
Using machine learning for the classification of the remaining useful cycles in Lithium-ion batteries
(2021)
Conference Proceeding
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search