Advanced Search
    ZHONG Wancai, SUN Kuoteng, LI Wenge. Development of UAV Detection Platform for Non-Contact Corrosion Detection of UHV Transmission Tower[J]. Corrosion & Protection, 2025, 46(11): 66-71. DOI: 10.11973/fsyfh240670
    Citation: ZHONG Wancai, SUN Kuoteng, LI Wenge. Development of UAV Detection Platform for Non-Contact Corrosion Detection of UHV Transmission Tower[J]. Corrosion & Protection, 2025, 46(11): 66-71. DOI: 10.11973/fsyfh240670

    Development of UAV Detection Platform for Non-Contact Corrosion Detection of UHV Transmission Tower

    • A intelligent non-contact corrosion detection scheme using unmanned aerial vehicle was proposed to address the problems of poor safety and low detection efficiency in traditional manual inspection of transmission towers. Based on the complex airspace working environment of drones in 500 kV ultra-high voltage transmission systems, the key parameters of drones were determined, and a scalable insulation rod mechanism was designed to achieve safe operation of drones in 500 kV ultra-high voltage electromagnetic fields. Aerodynamic and static stress simulation analysis was conducted on the drone, and the results showed that in the detection state where the telescopic pole was fully extended, the maximum force point of the drone was located in the contact area between the detection device and the long telescopic pole. The maximum deformation of the telescopic pole was 1.9 mm, the maximum stress was 38 MPa, and the y-axis center of gravity was offset by 83 mm. Field tests showed that when the drone was 1.5 m away from the 500 kV ultra-high voltage transmission and transformation tower, the drone detection platform could fly safely and stably near the ultra-high voltage tower. The detection instrument probe at the telescopic pole end was closest to the transmission tower at 10 cm, and the accuracy of corrosion layer thickness measurement reached 0.1 μm.
    • loading

    Catalog

      Turn off MathJax
      Article Contents

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return