Wind turbine inspection with drone: Advantages and disadvantages

被引:0
|
作者
Tanrıverdi H. [1 ]
Karakuş G. [2 ]
Ulukan A. [1 ]
机构
[1] Abdullah Gul University, Graduate School of Engineering and Science, Electrical and Computer Engineering, Kayseri
[2] Necmettin Erbakan University, Faculty of Aeronautics and Astronautics, Department of Aviation Management, Konya
来源
Journal of Energy Systems | 2023年 / 7卷 / 01期
关键词
Drone; Inspection; Maintenance; Turbine; Wind energy;
D O I
10.30521/jes.1148877
中图分类号
学科分类号
摘要
The facilities on wind energy generation are increasingly finding usage areas in line with the ecologically friendly energy generation approach. One of the important activities of wind power generation facilities, which have high investment cost, low operating cost and low environmental impact is the maintenance and repair of wind turbines. A preventive maintenance approach is dominant to reduce maintenance times and eliminate lost time in wind turbines. Damage inspection of turbines has been evolved from tower crane access, rope access, camera viewing, and other applications to image with manual drones over the years. However, when these methods are evaluated within the framework of criteria such as cost, performance, occupational safety and data reliability, they are still insufficient and the need for inspection with autonomous drones arises. The advantages and disadvantages of autonomous drones used in the determination of damage in wind turbines are analyzed and the results are considered to contribute to the practitioners operating in the sector and academicians working in the field. © 2023 Published by peer-reviewed open access scientific journal.
引用
收藏
页码:57 / 66
页数:9
相关论文
共 50 条
  • [1] SAMPLING INSPECTION BY ATTRIBUTES - ADVANTAGES AND DISADVANTAGES
    Klufa, Jindrich
    [J]. 11TH INTERNATIONAL DAYS OF STATISTICS AND ECONOMICS, 2017, : 703 - 711
  • [2] Wind Turbine Surface Damage Detection by Deep Learning Aided Drone Inspection Analysis
    Shihavuddin, A. S. M.
    Chen, Xiao
    Fedorov, Vladimir
    Christensen, Anders Nymark
    Riis, Nicolai Andre Brogaard
    Branner, Kim
    Dahl, Anders Bjorholm
    Paulsen, Rasmus Reinhold
    [J]. ENERGIES, 2019, 12 (04)
  • [3] Towards accurate image stitching for drone-based wind turbine blade inspection
    Yang, Cong
    Liub, Xun
    Zhou, Hua
    Ke, Yan
    See, John
    [J]. RENEWABLE ENERGY, 2023, 203 : 267 - 279
  • [4] Simultaneous drone localisation and wind turbine model fitting during autonomous surface inspection
    Moolan-Feroze, Oliver
    Karachalios, Konslanlinos
    Nikolaidis, Dimitrios N.
    Calway, Andrew
    [J]. 2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2019, : 2014 - 2021
  • [5] Review of Wind Models at a Local Scale: Advantages and Disadvantages
    Martinez-Garcia, Felix P.
    Contreras-de-Villar, Antonio
    Munoz-Perez, Juan J.
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2021, 9 (03)
  • [6] Advantages and Disadvantages
    不详
    [J]. WELDING JOURNAL, 2021, 100 (05) : 18 - 18
  • [7] Review on the Advancements in Wind Turbine Blade Inspection: Integrating Drone and Deep Learning Technologies for Enhanced Defect Detection
    Memari, Majid
    Shakya, Praveen
    Shekaramiz, Mohammad
    Seibi, Abdennour C.
    Masoum, Mohammad A. S.
    [J]. IEEE ACCESS, 2024, 12 (12): : 33236 - 33282
  • [8] Optimisation of Wind Turbine Inspection Intervals
    Andrawus, Jesse
    Watson, John
    Kishk, Mohammed
    Gordon, Heather
    [J]. WIND ENGINEERING, 2008, 32 (05) : 477 - 490
  • [9] Robot Inspection for Wind Turbine Blades
    朱盛榕
    [J]. 热能动力工程, 2019, 34 (12) : 7 - 7
  • [10] Drone Path Planning and Object Detection via QR Codes; A Surrogate Case Study for Wind Turbine Inspection
    Pinney, Branden
    Duncan, Shayne
    Shekaramiz, Mohammad
    Masoum, Mohammad A. S.
    [J]. 2022 INTERMOUNTAIN ENGINEERING, TECHNOLOGY AND COMPUTING (IETC), 2022,