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JACIII Vol.26 No.5 pp. 691-697
doi: 10.20965/jaciii.2022.p0691
(2022)

Paper:

A High-Precision Power Line Recognition and Location Method Based on Structured-Light Binocular Vision

Xu Jian*,†, Jinbin Li*, Xin Chen**,***, Xing-Ao Wang**,***, Jun Chen*, and Chuanqi Wu*

*Electric Power Research Institute, State Grid Hubei Electric Power Co., Ltd.
No.227 Xudong Street, Hongshan District, Wuhan 430077, China

**School of Automation, China University of Geosciences
No.388 Lumo Road, Hongshan District, Wuhan 430074, China

***Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
No.388 Lumo Road, Hongshan District, Wuhan 430074, China

Corresponding author

Received:
March 15, 2022
Accepted:
April 25, 2022
Published:
September 20, 2022
Keywords:
live working of power distribution, binocular vision, transmission line recognition, precise positioning
Abstract

To complete the wiring operation of the main transmission line stripped of its insulating skin in a live power distribution system, a structured-light binocular vision method is utilized to identify and locate the line. First, aiming at the interference of the background information, a depth threshold segmentation method is used to filter the background area. Second, a mean filtering method is proposed to filter out the mismatch noise of a binocular vision camera in an outdoor environment. The Canny algorithm is then utilized to extract the contour, the central axis of the main transmission line is fitted, and the difference in the neighborhood pixel value is used to recognize the stripping area. Finally, the spatial equation and attitude of the central axis of the fitting transmission line are obtained along with the central coordinates of the stripping area, guiding the robot to carry out the wiring.

The power line positioning method

The power line positioning method

Cite this article as:
X. Jian, J. Li, X. Chen, X. Wang, J. Chen, and C. Wu, “A High-Precision Power Line Recognition and Location Method Based on Structured-Light Binocular Vision,” J. Adv. Comput. Intell. Intell. Inform., Vol.26 No.5, pp. 691-697, 2022.
Data files:
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Last updated on Oct. 11, 2024