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Image Recognition of Icing Thickness on Power Transmission Lines Based on a Least Squares Hough Transform

Author

Listed:
  • Jingjing Wang

    (School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China)

  • Junhua Wang

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

  • Jianwei Shao

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

  • Jiangui Li

    (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China)

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.

Suggested Citation

  • Jingjing Wang & Junhua Wang & Jianwei Shao & Jiangui Li, 2017. "Image Recognition of Icing Thickness on Power Transmission Lines Based on a Least Squares Hough Transform," Energies, MDPI, vol. 10(4), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:415-:d:93819
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    References listed on IDEAS

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    1. Jianlin Hu & Caixin Sun & Xingliang Jiang & Daibo Xiao & Zhijin Zhang & Lichun Shu, 2012. "DC Flashover Performance of Various Types of Ice-Covered Insulator Strings under Low Air Pressure," Energies, MDPI, vol. 5(5), pages 1-23, May.
    2. Jianlin Hu & Caixin Sun & Xingliang Jiang & Qing Yang & Zhijin Zhang & Lichun Shu, 2011. "Model for Predicting DC Flashover Voltage of Pre-Contaminated and Ice-Covered Long Insulator Strings under Low Air Pressure," Energies, MDPI, vol. 4(4), pages 1-16, April.
    3. Jianlin Hu & Xingliang Jiang & Fanghui Yin & Zhijin Zhang, 2015. "DC Flashover Performance of Ice-Covered Composite Insulators with Parallel Air Gaps," Energies, MDPI, vol. 8(6), pages 1-17, May.
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    Cited by:

    1. Nermin Suljanović & Aljo Mujčić & Matej Zajc, 2017. "Communication Characteristics of Faulted Overhead High Voltage Power Lines at Low Radio Frequencies," Energies, MDPI, vol. 10(11), pages 1-24, November.
    2. Francisca Alcayde-García & Esther Salmerón-Manzano & Miguel A. Montero & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2022. "Power Transmission Lines: Worldwide Research Trends," Energies, MDPI, vol. 15(16), pages 1-21, August.
    3. Jeff Laninga & Ali Nasr Esfahani & Gevindu Ediriweera & Nathan Jacob & Behzad Kordi, 2023. "Monitoring Technologies for HVDC Transmission Lines," Energies, MDPI, vol. 16(13), pages 1-32, June.
    4. Ziquan Liu & Huifang Wang, 2018. "Automatic Detection of Transformer Components in Inspection Images Based on Improved Faster R-CNN," Energies, MDPI, vol. 11(12), pages 1-18, December.
    5. Ivan Kabardin & Sergey Dvoynishnikov & Maxim Gordienko & Sergey Kakaulin & Vadim Ledovsky & Grigoriy Gusev & Vladislav Zuev & Valery Okulov, 2021. "Optical Methods for Measuring Icing of Wind Turbine Blades," Energies, MDPI, vol. 14(20), pages 1-14, October.
    6. Yanpeng Hao & Jie Wei & Xiaolan Jiang & Lin Yang & Licheng Li & Junke Wang & Hao Li & Ruihai Li, 2018. "Icing Condition Assessment of In-Service Glass Insulators Based on Graphical Shed Spacing and Graphical Shed Overhang," Energies, MDPI, vol. 11(2), pages 1-12, February.

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