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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, email

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.

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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.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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