Based on the characteristics of low cost, easy control and high flexibility of drone, the application of drone in inspection of pole tower and power lines had become the best tool for efficiently and safely completing inspection operations, and had been widely used in power inspection. Traditional drone inspection require long-term flight control operation of drone, “drone crash into tower” and other accidents were also increasing with the expansion of business, the industry urgently needs the more intelligent, safe and controllable inspection operation. From this, “automatic drone power fine inspection solution” was proposed, firstly, the overall architecture design of the solution was introduced, including software and hardware design scheme, network architecture and data transmission mode. Then, the design scheme of the flight route for the fine inspection of the pole and tower was introduced, the flight path of the drone from the automatic drone port flight to the target pole tower was planned, and the single pole tower shooting scheme and multi-group pole tower shooting scheme were designed. Then it focuses on solving the problem that the key components such as insulators, damper and link fitting account for a relatively small proportion in the shooting scheme taken by drones, FPN (region generation network) was used to build Faster R-CNN (Regional Convolutional Neural Network) detection model to improve the efficiency and accuracy of hidden danger detection of small components. In the practical application case, the Bolt missing pin and other hidden defects identified by image recognition method of automatic drone in the task of pole tower inspection were introduced. The efficiency, accuracy, timely response and cost savings of this solution had been verified in field cases. The demonstration application scenario of automatic drone was formed through the functions of on-site deployment of mission, automatic drone takes-off and landing, automatic patrol, remote control to perform tasks.


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    Title :

    Research and Application of Intelligent Automatic Drone Port and Image Recognition in Precise Inspection of Pole Tower


    Additional title:

    Springer Aerospace Techn.


    Contributors:
    Liu, Zishun (editor) / Li, Renfu (editor) / He, Xiaodong (editor) / Zhu, Zhenghong (editor) / Gao, Fan (author) / Long, Zhongyi (author)

    Conference:

    International Conference on Advanced Unmanned Aerial Systems ; 2023 ; Harbin, China July 14, 2023 - July 16, 2023



    Publication date :

    2024-02-01


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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