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Abnormal target detection method of transmission line flaw detection robot based on X-ray image feature segmentation algorithm

Published: 31 July 2024 Publication History

Abstract

In order to improve the low success rate of abnormal target detection of transmission line inspection robot, an abnormal target detection method of transmission line inspection robot based on X-ray image feature segmentation algorithm is proposed. Establish the principle structure of X-ray image feature segmentation algorithm, and analyze the X-ray image feature segmentation algorithm; Locate the search node, establish the motion matrix of the transmission line inspection robot in the target area, determine the path planning evaluation function of the transmission line inspection robot, and realize the abnormal target detection of the transmission line inspection robot. The experimental results show that this method can accurately locate the abnormal target detection area of the transmission line flaw detection robot, and ensure the complete detection of all abnormal target detection points, and the position coordinates of these detection points are completely corresponding to the initial position coordinates, which has a higher detection success rate.

References

[1]
Cordell D, Unsworth M J, Lee B, Estimating the Geoelectric Field and Electric Power Transmission Line Voltage During a Geomagnetic Storm in Alberta, Canada Using Measured Magnetotelluric Impedance Data: The Influence of Three-Dimensional Electrical Structures in the Lithosphere[J]. Space weather, 2021, 19(10): 1-20.
[2]
Xiaoqiang S. Research on Construction Technology and Quality Control of Transmission Line in Electric Power Engineering[J]. Engineering and Technological, 2021(7): 785-787.
[3]
Daouda KonaneWend Yam Serge Boris OuedraogoToussaint Tilado GuinganeAbdoulaye ZongoZacharie KoalagaFranois Zougmoré.An Exact Solution of Telegraph Equations for Voltage Monitoring of Electrical Transmission Line[J]. Energy and Power Engineering, 2022, 14(11): 669-679.
[4]
Wei J, Hua Z D, Shuangbao M, Dynamic walking characteristics and control of four-wheel mobile robot on ultra-high voltage multi-split transmission line[J]. Transactions of the Institute of Measurement and Control, 2022, 44(6): 1309-1322.
[5]
Ohno M, Takeda Y. Design of target trajectories for the detection of joint clearances in parallel robot based on the actuation torque measurement[J]. Mechanism and Machine Theory, 2021, 155(1): 1-10.
[6]
Cen H. Target location detection of mobile robots based on R-FCN deep convolutional neural network[J]. International journal of systems assurance engineering and management, 2023, 14(2): 728-737.
[7]
Wang J, Xu T, Zhang L, Nondestructive damage evaluation of composites based on terahertz and X-ray image fusion[J]. NDT & E International: Independent Nondestructive Testing and Evaluation, 2022, 127(127): 1-11.
[8]
Jianqiao Y U, Hui L, Yi S. CT reconstruction from a single X-ray image for a particular patient via progressive learning[J]. Chinese Journal of Stereology and Image Analysis, 2022, 27(2): 96-112.
[9]
Urazoe K, Kuroki N, Maenaka A, Automated Fish Bone Detection in X-Ray Images with Convolutional NeuralNetwork and Synthetic Image Generation[J]. IEEJ Transactions on Electrical and Electronic Engineering, 2021, 16(11): 1510-1517.
[10]
Yao X T, Li Z Y, Cheng X. Research on Robot Path Planning Based on Improved Ant Colony Algorithm[J]. Computer Simulation, 2021, 38(11): 379-383.

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  1. Abnormal target detection method of transmission line flaw detection robot based on X-ray image feature segmentation algorithm

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    PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial Intelligence
    January 2024
    969 pages
    ISBN:9798400716638
    DOI:10.1145/3674225
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 31 July 2024

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