Transmission line bolts and their defects detection method based on position relationship

被引:1
|
作者
Zhao, Zhenbing [1 ,2 ,3 ]
Xiong, Jing [1 ,4 ]
Han, Yu [1 ]
Miao, Siyu [1 ]
机构
[1] North China Elect Power Univ, Sch Elect & Elect Engn, Baoding, Peoples R China
[2] North China Elect Power Univ, Engn Res Ctr Intelligent Comp Complex Energy Syst, Minist Educ, Baoding, Peoples R China
[3] North China Elect Power Univ, Hebei Key Lab Power Internet Things Technol, Baoding 071003, Peoples R China
[4] Sichuan Vocat & Tech Coll Commun, Dept Informat Engn, Chengdu, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
transmission line bolts; bolts defects; target detection; attention mechanism; positional relationship;
D O I
10.3389/fenrg.2023.1269087
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Introduction: To solve the problems of small proportion of bolts in aerial images of power transmission lines, small differences between classes, and difficulty in extracting refined features, this paper proposes a method for detecting power transmission line bolts and their defects based on positional relationships.Methods: Firstly, a spatial attention module is added to Faster R-CNN, using two parallel cross attention to obtain cross path features and global features respectively, and spatial feature enhancement is performed on the features output from the convolution layer. Then, starting from the spatial position relationship of bolts and their defects, using the relative geometric features of candidate regions as input, the spatial position relationship of bolts and their defects on the image is modeled. Finally, the position features and regional features are connected to obtain enhanced features. The bolt position knowledge on the connecting plate is added to the detection model to improve the detection accuracy of the model.Results and discussion: The experimental results show that the mAP value of the algorithm in this paper is increased by 6.61% compared to the Faster R-CNN detection model in aerial photography of transmission line bolts and their defect datasets, with the AP value of normal bolts increased by 1.73%, the AP value of pin losing increased by 4.45%, and the AP value of nut losing increased by 13.63%.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] Hybrid method for transient responses of transmission line in an apertured enclosure based on FETD method and transmission line equations
    Gong, Yanfei
    Jiang, Luhang
    IET SCIENCE MEASUREMENT & TECHNOLOGY, 2020, 14 (09) : 685 - 695
  • [42] METHOD OF ROCK BOLTS PARAMETERS DETECTION BASED ON HARMONIC WAVELET PACKET TRANSFORM
    Sun, Xiao-Yun
    Wang, Zhi-Yuan
    Kang, Feng-Ning
    Li, Wei-Fang
    PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOL. 2, 2015, : 678 - 683
  • [43] Trajectory Detection Method for Transmission Line Path Following Control
    Namorato Pusssente, Guilherme Augusto
    Santa Maria, Tiago Henrique
    Marques Marcato, Andre Luis
    de Aguiar, Eduardo Pestana
    2021 LATIN AMERICAN ROBOTICS SYMPOSIUM / 2021 BRAZILIAN SYMPOSIUM ON ROBOTICS / 2021 WORKSHOP OF ROBOTICS IN EDUCATION (LARS-SBR-WRE 2021), 2021, : 42 - 47
  • [44] Automatic diagnosis system of transmission line abnormalities and defects based on UAV
    Zhang, Fangzheng
    Wang, Wanguo
    Zhao, Yabo
    Li, Peng
    Lin, Qiaoyun
    Jiang, Lingao
    2016 4TH INTERNATIONAL CONFERENCE ON APPLIED ROBOTICS FOR THE POWER INDUSTRY (CARPI), 2016,
  • [45] A novel bottom-up keypoints based hexagon bolts detection method
    Wu, Yang
    Sun, Junhua
    AOPC 2020: DISPLAY TECHNOLOGY; PHOTONIC MEMS, THZ MEMS, AND METAMATERIALS; AND AI IN OPTICS AND PHOTONICS, 2020, 11565
  • [46] A Through-Transmission Ultrasonic Method for the Detection of Ferrite Tile Defects
    Huang, Kaiheng
    Li, Qiaolin
    Zhu, Kaixiong
    Chen, Baihan
    Qian, Xiang
    Wang, Xiaohao
    Li, Xinghui
    APPLIED SCIENCES-BASEL, 2023, 13 (20):
  • [47] A New Image Detection Method of Transmission Line Icing Thickness
    Zhang, Yuying
    Wang, Yonglan
    Wei, Aming
    PROCEEDINGS OF 2020 IEEE 4TH INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2020), 2020, : 2059 - 2064
  • [48] An Ultrasmall Bolt Defect Detection Method for Transmission Line Inspection
    Luo, Peng
    Wang, Bo
    Wang, Hongxia
    Ma, Fuqi
    Ma, Hengrui
    Wang, Leixiong
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
  • [49] Defect detection method for key area guided transmission line components based on knowledge distillation
    Zhao, Zhenbing
    Lv, Xuechun
    Xi, Yue
    Miao, Siyu
    FRONTIERS IN ENERGY RESEARCH, 2023, 11
  • [50] Attention Model and Soft-NMS-Based Transmission Line Small Target Detection Method
    Zhao Y.
    Tian S.
    Li Y.
    Luo L.
    Qi P.
    Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China, 2023, 52 (06): : 906 - 914