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Research and Application of a Smart Monitoring System to Monitor the Deformation of a Dam and a Slope

Authors :
Yongfei Wang
Dingbin Shen
Jiankang Chen
Liang Pei
Yanling Li
Xiang Lu
Lei Zhang
Source :
Advances in Civil Engineering, Vol 2020 (2020)
Publication Year :
2020
Publisher :
Wiley, 2020.

Abstract

Deformation monitoring is one of the most important means of providing feedback to ensure the safety of projects. Problems plague the existing automatic monitoring system, such as the small monitoring range of monitoring devices, the inadequate field safety protection, and the low accuracy under extreme weather conditions. These problems greatly reduce the real time and reliability of deformation monitoring data and restrict the real-time intelligent control of engineering safety risk. In this paper, a multitype instrument-integrated monitoring system based mainly on the total positioning station (TPS) and supplemented by the Global Navigation Satellite System (GNSS) was promoted with the methods of large field angle, data complementation, environmental perception and judgment, automatic status control, and baseline calibration-meteorological fusion correction. The application results of Pubugou Station show that the averages of mean square error of points (APMSE) for the dam are 0.41∼1.65 mm and the averages of mean square error of height (AHMSE) are 0.42∼0.89 mm. Moreover, the APMSE and AHMSE for the slope are less than 3 mm. The maximum relative error of the TPS and GNSS data compared with the artificial monitoring data is less than 10%. Besides, the system has good overall performance and is of significant comprehensive benefits. The proposed system realizes the all-weather real-time monitoring of deformation and enhances the emergency response capability of special conditions in dams during the operation period.

Details

Language :
English
ISSN :
16878086 and 16878094
Volume :
2020
Database :
Directory of Open Access Journals
Journal :
Advances in Civil Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.33e6e1ae0e9244369b955218669e409c
Document Type :
article
Full Text :
https://doi.org/10.1155/2020/9709417