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Cited by 160Power Line Inspection RobotsUAV Applications and OptimizationInfrastructure Maintenance and Monitoring

Design and Application of a UAV Autonomous Inspection System for High-Voltage Power Transmission Lines

Open access
Li, Ziran, Zhang, Yanwen, Wu, Hao, Suzuki, Satoshi, Namiki, Akio, Wang, Wei·2023·Remote Sensing
DOI 10.3390/rs15030865
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Abstract

As the scale of the power grid continues to expand, the human-based inspection method struggles to meet the needs of efficient grid operation and maintenance. Currently, the existing UAV inspection system in the market generally has short endurance power time, high flight operation requirements, low degree of autonomous flight, low accuracy of intelligent identification, slow generation of inspection reports, and other problems. In view of these shortcomings, this paper designs an intelligent inspection system based on self-developed UAVs, including autonomous planning of inspection paths, sliding film control algorithms, mobile inspection schemes and intelligent fault diagnosis. In the first stage, basic data such as latitude, longitude, altitude, and the length of the cross-arms are obtained from the cloud database of the power grid, while the lateral displacement and vertical displacement during the inspection drone operation are calculated, and the inspection flight path is generated independently according to the inspection type. In the second stage, in order to make the UAV’s flight more stable, the reference-model-based sliding mode control algorithm is introduced to improve the control performance. Meanwhile, during flight, the intelligent UAV uploads the captured photos to the cloud in real time. In the third stage, a mobile inspection program is designed in order to improve the inspection efficiency. The transfer of equipment is realized in the process of UAV inspection. Finally, to improve the detection accuracy, a high-precision object detector is designed based on the YOLOX network model, and the improved model increased the mAP0.5:0.95 metric by 2.22 percentage points compared to the original YOLOX_m for bird’s nest detection. After a large number of flight verifications, the inspection system designed in this paper greatly improves the efficiency of power inspection, shortens the inspection cycle, reduces the investment cost of inspection manpower and material resources, and successfully fuses the object detection algorithm in the field of high-voltage power transmission lines inspection.

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  • Publications [4,5,6,7,8,9,10] address techniques for carrying out preventive inspections on transmission lines using RPASs with thermal cameras, demonstrating the importance of using this technology and the impact of using aircraft to carry out inspections.

    “Publications [4,5,6,7,8,9,10] address techniques for carrying out preventive inspections on transmission lines using RPASs with thermal cameras, demonstrating the importance of using this technology and the impact of using aircraft to carry out inspections.”

    From Multicriteria Methodology for Prioritizing Predictive Maintenance Using RPASs (Drones) with Thermal Cameras on Transmission Lines (2025) · cites this paper as [6]

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • The first studies, especially [6,9], provide an important basis for better understanding the thermographic inspection technique using drones, also showing how image processing helps identify defects.

    “The first studies, especially [6,9], provide an important basis for better understanding the thermographic inspection technique using drones, also showing how image processing helps identify defects, which are delegated to maintenance teams to resolve.”

    From Multicriteria Methodology for Prioritizing Predictive Maintenance Using RPASs (Drones) with Thermal Cameras on Transmission Lines (2025) · cites this paper as [6]

    Section 3.1 describes drone photographs being reviewed with manual and deep-learning methods, followed by reports that staff use to arrange maintenance. But it says the automated method mainly detects bird’s nests, while line defects are reviewed manually; the Discussion confirms that the deployed algorithm cannot yet detect other line defects. The cited passages do not establish a thermographic inspection technique. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Li, Z., Zhang, Y., Wu, H., Suzuki, S., Namiki, A., & Wang, W.
Affiliations
  • Chiba University (JP)
  • Nanjing University of Information Science and Technology (CN)
Corresponding author
Wang, Wei
ORCID
Venue
Remote Sensing
Publisher
MDPI AG
Published
2023-02-03
Volume
15
Issue
3
Pages
865
ISSN
2072-4292 (ISSN-L)
DOI
10.3390/rs15030865
OpenAlex
W4319315490
Cited by
160
References
5
Citations by year
2026: 39 · 2025: 60 · 2024: 42 · 2023: 19
FWCI
15.77
Type
journal article
Language
en
Open access
Licence
Locations
  • Remote Sensing (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Japan Society for the Promotion of Science (23K22710)
Topics
  • Physical Sciences › Engineering › Mechanical Engineering › Power Line Inspection Robots
  • Physical Sciences › Engineering › Aerospace Engineering › UAV Applications and Optimization
  • Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
Keywords
UAV inspection, high-voltage transmission lines, sliding mode control, fault diagnosis, power grid inspection

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