• Acta Optica Sinica
  • Vol. 43, Issue 21, 2112002 (2023)
Yueqiang Zhang1、2, Mingjie Chen1、2, Biao Hu1、2、*, Wenjun Chen1、2, Yihe Yin1、2, Qifeng Yu1、2, and Xiaolin Liu1、2
Author Affiliations
  • 1Institute of Intelligent Optical Measurement and Detection, Shenzhen University, Shenzhen 518000, Guangdong , China
  • 2College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518000, Guangdong , China
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    DOI: 10.3788/AOS230784 Cite this Article Set citation alerts
    Yueqiang Zhang, Mingjie Chen, Biao Hu, Wenjun Chen, Yihe Yin, Qifeng Yu, Xiaolin Liu. Transmission Mechanism and Suppression Methods of Measurement Error Based on Camera Networking[J]. Acta Optica Sinica, 2023, 43(21): 2112002 Copy Citation Text show less
    Schematic diagram of serial camera network based on displacement transmission
    Fig. 1. Schematic diagram of serial camera network based on displacement transmission
    Sketch map of camera network basic configuration
    Fig. 2. Sketch map of camera network basic configuration
    Numerical simulation procedure of camera network
    Fig. 3. Numerical simulation procedure of camera network
    Statistical results of camera network basic configuration. (a) Average value; (b) root mean square error
    Fig. 4. Statistical results of camera network basic configuration. (a) Average value; (b) root mean square error
    Influence of camera station number on transmission error
    Fig. 5. Influence of camera station number on transmission error
    Influence of subsidence amplitude and inclination angle on transmission error
    Fig. 6. Influence of subsidence amplitude and inclination angle on transmission error
    Influence of benchmark position on transmission error. (a) Root mean square error; (b) condition number of survey matrix (color of grid in picture represents magnitude of corresponding dependent variable. Magnitude that color represents corresponds to color bar on right side of picture)
    Fig. 7. Influence of benchmark position on transmission error. (a) Root mean square error; (b) condition number of survey matrix (color of grid in picture represents magnitude of corresponding dependent variable. Magnitude that color represents corresponds to color bar on right side of picture)
    Influence of distance between camera station and benchmark position (D1) on transmission error. (a) Changing distance between camera station and benchmark position on one side of network; (b) changing distance between camera station and benchmark position simultaneously on both sides of network
    Fig. 8. Influence of distance between camera station and benchmark position (D1) on transmission error. (a) Changing distance between camera station and benchmark position on one side of network; (b) changing distance between camera station and benchmark position simultaneously on both sides of network
    Sketch map of survey mark distribution between camera stations
    Fig. 9. Sketch map of survey mark distribution between camera stations
    Influence of survey mark position on transmission error. (a) Root mean square error; (b) condition number of survey matrix (color of grid in picture represents magnitude of corresponding dependent variable. Magnitude that color represents corresponds to color bar on right side of picture)
    Fig. 10. Influence of survey mark position on transmission error. (a) Root mean square error; (b) condition number of survey matrix (color of grid in picture represents magnitude of corresponding dependent variable. Magnitude that color represents corresponds to color bar on right side of picture)
    Influence of survey mark number on transmission error
    Fig. 11. Influence of survey mark number on transmission error
    Relationship between transmission error and error coefficient of camera network. (a) Influence of benchmark position; (b) influence of survey mark position
    Fig. 12. Relationship between transmission error and error coefficient of camera network. (a) Influence of benchmark position; (b) influence of survey mark position
    Validation experiment of camera network on long-span cable-stayed bridge
    Fig. 13. Validation experiment of camera network on long-span cable-stayed bridge
    Monitoring results of cable-stayed bridge camera network with different network configurations (Cf1-Cf6 represent network configurations 1-6 respectively in Table 4)
    Fig. 14. Monitoring results of cable-stayed bridge camera network with different network configurations (Cf1-Cf6 represent network configurations 1-6 respectively in Table 4)
    ParameterNotationValue
    Number of simulation cyclesn'5×104
    Spacing between marksD20 m
    Calibration error of scaling factorεc1%
    Feature extraction errorεe0.5 pixel
    Amplitude of subsidences100 mm
    Angle of inclinationθ5'
    Table 1. System parameters of camera network basic configuration
    Network configurationInstruction3 camera stations5 camera stations7 camera stations
    σ/mm /%σ/mm /%σ/mm /%
    02 uniformly-spaced survey marks between camera stations2.8805.7209.150
    1Set cameras at benchmark on both sides0.9567.025.1010.858.793.93
    25 uniformly-spaced survey marks between camera stations1.5944.802.8749.794.4651.22
    3Set survey marks on camera stations1.0164.871.7968.772.7869.66
    4Configurations 1+30.6676.911.6371.572.6271.33
    5Configurations 2+31.0264.401.7270.012.5771.95
    6Configurations 1+2+30.5979.441.4874.082.4073.83
    Table 2. Comparison of camera network optimization with different camera stations
    Resolution /pixelFrame rate /(frame·s-1SensorPixel size /μmFocal length /mm
    2448×2048362/3",Sony IMX2643.45×3.45400
    Table 3. Parameters of experimental camera
    ConfigurationInstructionσ/mm
    1Set marks on benchmarks;2 marks between stations10.14
    2Set marks on benchmarks;3 marks between stations9.41
    3Set cameras on benchmarks;2 marks between stations3.13
    4Set cameras on benchmarks;3 marks between stations2.58
    5

    Set cameras on benchmarks;2 marks between stations;

    set marks on stations

    3.07
    6

    Set cameras on benchmarks;3 marks between stations;

    set marks on stations

    2.11
    Table 4. Bridge monitoring results of different error suppression methods
    Yueqiang Zhang, Mingjie Chen, Biao Hu, Wenjun Chen, Yihe Yin, Qifeng Yu, Xiaolin Liu. Transmission Mechanism and Suppression Methods of Measurement Error Based on Camera Networking[J]. Acta Optica Sinica, 2023, 43(21): 2112002
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