• Acta Photonica Sinica
  • Vol. 51, Issue 3, 0306004 (2022)
Xiangxin SHAO, Zixiao MA, Tianqi LU, Dong LI, and Hong JIANG*
Author Affiliations
  • School of Electrical and Electronic Engineering ,Changchun University of Technology,Changchun 130012,China
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    DOI: 10.3788/gzxb20225103.0306004 Cite this Article
    Xiangxin SHAO, Zixiao MA, Tianqi LU, Dong LI, Hong JIANG. Design of Cobweb Fiber Bragg Grating Sensor Network Based on Gated Circulation Unit[J]. Acta Photonica Sinica, 2022, 51(3): 0306004 Copy Citation Text show less
    Workflow of sensing system
    Fig. 1. Workflow of sensing system
    Topology of sensor network
    Fig. 2. Topology of sensor network
    Block diagram of sensor network system
    Fig. 3. Block diagram of sensor network system
    Overlapping types of FBG reflection spectra
    Fig. 4. Overlapping types of FBG reflection spectra
    Unit structure of the GRU
    Fig. 5. Unit structure of the GRU
    Schematic diagram of cobweb network fault self-healing
    Fig. 6. Schematic diagram of cobweb network fault self-healing
    GRU algorithm training process
    Fig. 7. GRU algorithm training process
    Test results of the training model under five overlapping conditions
    Fig. 8. Test results of the training model under five overlapping conditions
    Wavelength values of four FBG under different measured strain values in the GRU model
    Fig. 9. Wavelength values of four FBG under different measured strain values in the GRU model
    CaseD1,D2,and D3 operationsCan CO receive the reflection spectrum of F primeSchematic color
    Fault1Disconnect:D1 inputYesRed
    Fault2Disconnect:D1 input and outputYesBlue
    Fault3Disconnect:D1 input/output,D2 inputYesGreen
    Fault4Disconnect:D1 input/output,D2 input/outputNoPurple
    Table 1. Experimental results of cobweb network reliability
    Layer (type)Output shapeParam #

    Total params:2,717,454

    Trainable params:2,717,454

    Non-trainable params:0

    gru (GRU)(None,50,500)783 000
    gru_1 (GRU)(None,50,500)1 503 000
    gru_2 (GRU)(None,200)421 200
    dropout (Dropout)(None,200)0
    dense (Dense)(None,50)10 050
    dense_1 (Dense)(None,4)204
    Table 2. This paper summarizes the algorithm model
    CasePredictedTrue

    RMSE/

    pm

    λB1/nmλB2/nmλB3/nmλB4/nmλB1/nmλB2/nmλB3/nmλB4/nm
    a1 552.748 9011 552.924 8421 553.314 9411 553.705 131 552.751 552.9251 553.3151 553.7050.559 8
    b1 553.001 0341 552.924 8361 553.314 9511 553.705 1251 5531 552.9251 553.3151 553.7050.527 8
    c1 553.251 2261 552.924 8491 553.314 9631 553.705 121 553.251 552.9251 553.3151 553.7050.620 8
    d1 553.500 8111 552.924 8571 553.314 9821 553.705 1131 553.51 552.9251 553.3151 553.7050.415 9
    e1 553.748 8991 552.924 8621 553.314 9831 553.705 0981 553.751 552.9251 553.3151 553.7050.557 0
    Table 3. Spectral demodulation results for different overlap condition
    Xiangxin SHAO, Zixiao MA, Tianqi LU, Dong LI, Hong JIANG. Design of Cobweb Fiber Bragg Grating Sensor Network Based on Gated Circulation Unit[J]. Acta Photonica Sinica, 2022, 51(3): 0306004
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