• Laser & Optoelectronics Progress
  • Vol. 59, Issue 13, 1300005 (2022)
Chao Han, Binxin Hu*, Feng Zhu, Guangdong Song, Hua Zhang, Tieniu Li, and Chengquan Yang
Author Affiliations
  • Laser Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250300, Shandong , China
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    DOI: 10.3788/LOP202259.1300005 Cite this Article Set citation alerts
    Chao Han, Binxin Hu, Feng Zhu, Guangdong Song, Hua Zhang, Tieniu Li, Chengquan Yang. Review on Progress of High-Precision Demodulation Algorithm of Fiber Bragg Grating[J]. Laser & Optoelectronics Progress, 2022, 59(13): 1300005 Copy Citation Text show less
    Physical structure diagram of fiber grating
    Fig. 1. Physical structure diagram of fiber grating
    Diagram of fiber grating demodulation system based on tunable laser
    Fig. 2. Diagram of fiber grating demodulation system based on tunable laser
    Gaussian fitting model and actual waveform of FBG reflection spectrum. (a) Gaussian fitting model; (b) actual waveform
    Fig. 3. Gaussian fitting model and actual waveform of FBG reflection spectrum. (a) Gaussian fitting model; (b) actual waveform
    Error schematic of two algorithms. (a) Direct peak-finding algorithm; (b) power weighting algorithm
    Fig. 4. Error schematic of two algorithms. (a) Direct peak-finding algorithm; (b) power weighting algorithm
    Schematic diagram of Gaussian fitting algorithm
    Fig. 5. Schematic diagram of Gaussian fitting algorithm
    Comparison of Gaussian fitting and Gaussian-LM algorithm fitting[56]
    Fig. 6. Comparison of Gaussian fitting and Gaussian-LM algorithm fitting[56]
    Calibration of true value central wavelength and comparison of Gaussian and Gaussian-LM algorithmsl56]
    Fig. 7. Calibration of true value central wavelength and comparison of Gaussian and Gaussian-LM algorithmsl56]
    Schematic diagram of three-point peak-finding algorithm[58]
    Fig. 8. Schematic diagram of three-point peak-finding algorithm[58]
    Convolution results of Gaussian template and its first- and second-order differential forms with the original spectral signal[53]
    Fig. 9. Convolution results of Gaussian template and its first- and second-order differential forms with the original spectral signal[53]
    FBG sensor network demodulation system diagram
    Fig. 10. FBG sensor network demodulation system diagram
    Results of Hilbert transform[64]. (a) Smoothed spectrum signal; (b) Hilbert transformed spectrum signal
    Fig. 11. Results of Hilbert transform[64]. (a) Smoothed spectrum signal; (b) Hilbert transformed spectrum signal
    Demodulation results of different types of distortion of FBG[41]. (a) Light intensity attenuation; (b) spectral broadening; (c) spectral asymmetry
    Fig. 12. Demodulation results of different types of distortion of FBG[41]. (a) Light intensity attenuation; (b) spectral broadening; (c) spectral asymmetry
    AlgorithmDemodulation accuracyAnti-noise performanceEvaluation
    Direct peak-findingLowLowHigher requirements on the number of sampled spectral points
    Power weighting algorithm (centroid method)LowLowPeak-seeking error will be reduced in the case of low noise
    General polynomial fittingMiddleLowAccuracy is with regard to the observed data. If the peak value is not within the sampling point, the error will be large
    Gaussian fitting algorithmHighHighStrict requirements on spectrum
    Gaussian-polynomial fitting algorithmMiddleLowAccuracy is with regard to the observed data. If the peak value is not within the sampling point, the error will be large
    Gaussian nonlinear curve fitting algorithmHighHighBe not applicable to actual situation
    Table 1. Summary of six traditional fiber grating demodulation algorithms
    Chao Han, Binxin Hu, Feng Zhu, Guangdong Song, Hua Zhang, Tieniu Li, Chengquan Yang. Review on Progress of High-Precision Demodulation Algorithm of Fiber Bragg Grating[J]. Laser & Optoelectronics Progress, 2022, 59(13): 1300005
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