LAPSE:2019.1480
Published Article
LAPSE:2019.1480
Image Recognition of Icing Thickness on Power Transmission Lines Based on a Least Squares Hough Transform
Jingjing Wang, Junhua Wang, Jianwei Shao, Jiangui Li
December 10, 2019
In view of the shortcomings of current image detection methods for icing thickness on power transmission lines, an image measuring method for icing thickness based on remote online monitoring was proposed. In this method, a Canny operator is used to get the image edge, in addition, a Hough transform and least squares are combined to solve the problems of traditional Hough transform in the parameter space whereby it is easily disturbed by the image background and noises, and eventually the edges of iced power transmission lines and un-iced power transmission lines are accurately detected in images which have low contrast, complex grayscale, and many noises. Furthermore, based on the imaging principle of the camera, a new geometric calculation model for icing thickness is established by using the radius of power transmission line as a reference, and automatic calculation of icing thickness is achieved. The results show that proposed image recognition method is rarely disturbed by noises and background, the image recognition results show good agreement with the real edges of iced power transmission lines and un-iced power transmission lines, and is simple and easy to program, which suggests that the method can be used for image recognition and calculation of icing thickness.
Keywords
geometric calculation model, Hough transform, icing thickness, least squares, power transmission line
Suggested Citation
Wang J, Wang J, Shao J, Li J. Image Recognition of Icing Thickness on Power Transmission Lines Based on a Least Squares Hough Transform. (2019). LAPSE:2019.1480
Author Affiliations
Wang J: School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Wang J: School of Electrical Engineering, Wuhan University, Wuhan 430072, China [ORCID]
Shao J: School of Electrical Engineering, Wuhan University, Wuhan 430072, China
Li J: School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
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Journal Name
Energies
Volume
10
Issue
4
Article Number
E415
Year
2017
Publication Date
2017-03-23
Published Version
ISSN
1996-1073
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PII: en10040415, Publication Type: Journal Article
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LAPSE:2019.1480
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doi:10.3390/en10040415
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Dec 10, 2019
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Calvin Tsay
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