Open Access
ARTICLE
Meteorological Correction Model of IBIS-L System in the Slope Deformation Monitoring
Xiaoqing Zuoa, Hongchu Yua, Chenbo Zib, Xiaokun Xub, Liqi Wangb, Haibo Liub
a Faculty of Land and Resource Engineering, Kunming University of Science and Technology, Yunnan Province, China;
b Huaneng Lancang River Hydropower CO., LTD, Kunming City, Yunan Province, China
* Corresponding Author: Hongchu Yu,
Intelligent Automation & Soft Computing 2018, 24(1), 47-54. https://doi.org/10.1080/10798587.2016.1267240
Abstract
Micro deformation monitoring system (IBIS-L) using high frequency microwave as signal for transmission,
is easily affected by meteorology. How to eliminate the meteorological influence effectively, and
extract useful information from the big data becomes a key to monitor the slope deformation with
high precision by the IBIS-L system. Evaluation of the optimum meteorological correction mode for
Slope Deformation Monitoring to ensure the accuracy of measurement is considered. This objective
was realized by model construction technology, which uses calculation formula of Microwave
Refraction rate, and the radial distance from the target point to the IBIS-L system to estimate the
irreal displacement by meteorological influence. In this paper we examine feasibility and accuracy of
the meteorological correction model via experiment analysis. This experiment takes the Nuozhadu
hydropower station slope monitoring for example. Firstly, the temperature, humidity, air pressure
and other meteorological parameters were measured simultaneously with IBIS-L system monitoring.
Secondly, the measured meteorological parameters were taken into calculation formula of Microwave
Refraction rate. Thirdly, combined with the radial distance from the target point to the IBIS-L system,
the meteorological correction model in using IBIS-L system for slope deformation monitoring was
established.
Keywords
Cite This Article
X. Zuo, H. Yu, C. Zi, X. Xu, L. Wang
et al., "Meteorological correction model of ibis-l system in the slope deformation monitoring,"
Intelligent Automation & Soft Computing, vol. 24, no.1, pp. 47–54, 2018.