Abstract
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.
Highlights
IntroductionWith global abnormal weather occurring frequently in today’s climate, icing disasters on power transmission lines are growing in frequency due to the prevailing macroclimate, micrometeorological, and microtopography conditions
The earliest reports of icing accidents on power transmission lines appeared in 1932, and since Norway, Canada, Britain, Russia, Japan and other countries or regions have had serious icing disasters.With global abnormal weather occurring frequently in today’s climate, icing disasters on power transmission lines are growing in frequency due to the prevailing macroclimate, micrometeorological, and microtopography conditions
The image recognition algorithm based on least squares Hough transform can accurately detect power transmission line edge
Summary
With global abnormal weather occurring frequently in today’s climate, icing disasters on power transmission lines are growing in frequency due to the prevailing macroclimate, micrometeorological, and microtopography conditions. These seriously threaten the safe operation of the power grid and have caused huge losses to the respective national economies. Transmission tower toppling, ice flashover, power transmission line galloping, etc., caused by icing, often occurred in China during the winter, [1,2,3]. Grid were 10.4 billion and 5 billion RMB, and the indirect economic losses and social impact caused by the power outage were more difficult to estimate [4,5,6]. In order to ensure the normal operation of the power system, reduce and prevent icing disaster consequences on power transmission lines, it is necessary achieve real-time online monitoring of icing thickness on these lines
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