| Issue |
E3S Web Conf.
Volume 165, 2020
2020 2nd International Conference on Civil Architecture and Energy Science (CAES 2020)
|
|
|---|---|---|
| Article Number | 03011 | |
| Number of page(s) | 5 | |
| Section | Geology, Mapping, and Remote Sensing | |
| DOI | https://doi.org/10.1051/e3sconf/202016503011 | |
| Published online | 01 May 2020 | |
Research on the Tower Pole Tilt Mechanism and Risk Assessment Technology Based on BeiDou reverse network RTK
1 Live work branch Company, Yunnan Power Grid Company ltd., Kunming, 650000, China
2 School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
3 School of Geodesy and Geomatics, Anhui University of Science and Technology, Huainan, 232001, China
4 Jiangsu Kebo Space Information Technology Co., Ltd., Nanjing, China
* Corresponding author: 1320013106@qq.com
In order to solve the problems of inaccurate and untimely monitoring and high false alarm rate in the current monitoring of the tower pole tilt attitude, this paper proposes a technology for monitoring the tower pole tilt attitude based on RTK technology of Beidou reverse network. This method uses reverse network RTK differential positioning algorithm, which can improve the positioning accuracy of the low-cost Beidou/GNSS positioning terminal and make the positioning accuracy of the tower pole tilt monitoring reach the millimeter level. In this paper, the tilt attitude information of the transmission line tower is measured and calculated by using the height and position information of the transmission line tower, and then the risk assessment is carried out, so as to control the tilt attitude and assess the risk of the transmission line tower. The actual test results show that the method can obtain the information of the tilt attitude of transmission tower pole accurately and reliably, and can be used to evaluate it, which meets the requirements of intelligent, accurate and digital management.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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