Fiber-Optic Gyroscope Thermal Calibration through Two-Dimensional N-Order Polynomial for Landslide Displacement Monitoring

Guiying Lu, Huiming Tang (), Yu Zhu, Yongquan Zhang and Haifeng Xu
Additional contact information
Guiying Lu: School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China
Huiming Tang: Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
Yu Zhu: School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China
Yongquan Zhang: Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
Haifeng Xu: School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China

Energies, 2022, vol. 15, issue 21, 1-17

Abstract: A fiber-optic gyroscope (FOG) with lower precision but higher cost advantage is typically selected according to working conditions and engineering budget. Thermal drift is the main factor affecting FOG precision. External thermal calibration methods by algorithms can effectively weaken the influence of thermal drift. This paper presents a thermal calibration method of a two-dimensional N-order polynomial (TDNP) and compares it with artificial neural network (ANN) methods to determine a software FOG thermal calibration method for landslide displacement monitoring. The TDNP thermal calibration coefficient matrix was established, and the thermal calibration capability of the TDNP method with different orders N was evaluated on the basis of error analysis. The ANN model with 1 to 18 hidden neural layers was established on the basis of LM, BR, and SCG algorithms to choose a suitable ANN. Finally, the mean absolute errors of FOG thermal calibration through the TDNP with different orders and the LM were compared. This method was applied in the Huangtupo landslide area, China. The results highlight that the TDNP method with order 5 had better performance and satisfied the requirements of landslide displacement monitoring. The research results can compensate for the lack of adaptability of the FOG thermal calibration method in landslide displacement monitoring.

Keywords: fiber-optic gyroscope; thermal calibration algorithm; two-dimensional N-order polynomial; artificial neural network; landslide displacement monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/21/7845/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/21/7845/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:21:p:7845-:d:950836

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().