The Center of the Circle Fitting Optimization Algorithm Based on the Hough Transform for Crane

被引:4
作者
Zhao, Chengli [1 ]
Fan, Chenyang [2 ,3 ,4 ]
Zhao, Zhangyan [1 ]
机构
[1] Wuhan Univ Technol, Sch Transportat & Logist Engn, Wuhan 430063, Peoples R China
[2] CCCC Second Harbor Engn Co Ltd, Wuhan 430040, Peoples R China
[3] Key Lab Large Span Bridge Construct Technol, Wuhan 430040, Peoples R China
[4] Res & Dev Ctr Transport Ind Intelligent Mfg Techn, Wuhan 430040, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 20期
关键词
circle; Hough transform; crane; photogrammetry; distortion;
D O I
10.3390/app122010341
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The basic principle of photogrammetry is mature and widely used in engineering. For gantry cranes, the base of which is usually a cylinder, the measurement of the center of the cylinder cross section is difficult, but its coordinates have an important impact on the safety evaluation of cranes. Aiming at the problem of measuring the center of a circle, an optimization method of fitting the center of a circle based on photogrammetry and the Hough transform is proposed. In this algorithm, the effect of image point distortion on the measurement accuracy is considered, and the similarity between ideal and actual midperpendicular is compared in the Hough space. The similarity is taken as the weight of the midperpendicular, and the space coordinates of the center of the circle are fitted again. This process needs to iterate repeatedly until convergence, and the fitting accuracy of the equal weighted midperpendicular fitting algorithm and the weighted midperpendicular fitting algorithm is compared. Finally, according to the characteristics of the algorithm, a theoretical verification experiment and an engineering experiment are carried out. The experimental results show that the proposed weighted midperpendicular fitting algorithm has a better effect than the equal weighted midperpendicular fitting algorithm, which obviously improves the fitting accuracy of the center of the circle and has high engineering value. In both experiments, the relative error was less than one percent. Especially in the engineering experiments, the weighted midperpendicular algorithm improved accuracy by an order of magnitude. Therefore, the proposed algorithm significantly improves the fitting accuracy of the center of the circle and effectively solves the difficulty that the center of the circle cannot be directly measured on the construction machinery.
引用
收藏
页数:16
相关论文
共 31 条
  • [1] Comparing the probing systems of coordinate measurement machine: Scanning probe versus touch-trigger probe
    Bastas, Ali
    [J]. MEASUREMENT, 2020, 156
  • [2] Burge J.H., 2007, Proc. of SPIE, V6676
  • [3] Cheng X., 2002, THESIS TONGJI U SHAN
  • [4] Least squares fitting of circles
    Chernov, N
    Lesort, C
    [J]. JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2005, 23 (03) : 239 - 252
  • [5] A Novel Hough Transform Algorithm for Multi-objective Detection
    Fei Rong
    Cui Duwu
    Hu Bo
    [J]. 2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 3, PROCEEDINGS, 2009, : 705 - +
  • [6] Grepl J, 2016, PROCEEDINGS OF THE 2016 17TH INTERNATIONAL CARPATHIAN CONTROL CONFERENCE (ICCC), P218, DOI 10.1109/CarpathianCC.2016.7501097
  • [7] Active anti-sway crane control using partial state feedback from inertial sensor
    Helma, Vaclav
    Goubej, Martin
    [J]. PROCESS CONTROL '21 - PROCEEDING OF THE 2021 23RD INTERNATIONAL CONFERENCE ON PROCESS CONTROL (PC), 2021, : 137 - 142
  • [8] Huang G., 2016, Theory, Method and Application of Digital Close Range Industrial Photogrametry
  • [9] Crane safety standards: Problem analysis and safety assurance planning
    Im, Sujung
    Park, Dugkeun
    [J]. SAFETY SCIENCE, 2020, 127 (127)
  • [10] Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?
    Kruger, Norbert
    Janssen, Peter
    Kalkan, Sinan
    Lappe, Markus
    Leonardis, Ales
    Piater, Justus
    Rodriguez-Sanchez, Antonio J.
    Wiskott, Laurenz
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (08) : 1847 - 1871