Yang, Yongsheng, Wang, Minzhen, Wang, Xinheng 
ORCID: 0000-0001-8771-8901, Li, Cheng, Shang, Ziwen and Zhao, Liying
(2023)
A Novel Monocular Vision Technique for the Detection of Electric Transmission Tower Tilting Trend.
APPLIED SCIENCES-BASEL, 13 (1).
p. 407.
Abstract
<jats:p>Transmission lines are primarily deployed overhead, and the transmission tower, acting as the fulcrum, can be affected by the unbalanced force of the wire and extreme weather, resulting in the transmission tower tilt, deformation, or collapse. This can jeopardize the safe operation of the power grid and even cause widespread failures, resulting in significant economic losses. Given the limitations of current tower tilt detection methods, this paper proposes a tower tilt detection and analysis method based on monocular vision images. The monocular camera collects the profile and contour features of the tower, and the tower tilt model is combined to realize the calculation and analysis of the tower tilt. Through this improved monocular visual monitoring method, the perception accuracy of the tower tilt is improved by 7.5%, and the axial eccentricity is accurate to ±2 mm. The method provides real-time reliability and simple operation for detecting tower inclination, significantly reducing staff inspection intensity and ensuring the power system operates safely and efficiently.</jats:p>
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | electric power transmission line, pole, image processing, monocular vision |
| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 21 Apr 2023 14:53 |
| Last Modified: | 17 Mar 2024 16:04 |
| DOI: | 10.3390/app13010407 |
| Open Access URL: | https://doi.org/10.3390/app13010407 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3169873 |
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