Optimal frequency scanning range for parameters extraction from Brillouin scattering spectrum

Zhi-niu, XU; Hu, Zhiwei; Zhao, Lijuan; Li, Yongqian

doi:10.1016/j.ijleo.2018.01.016

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Generally, the Brillouin gain spectrum is considered as a Voigt spectral shape [ 17 , 18 , 19 ]. Because the Lorentzian and Gaussian profiles are algebraic equations, key parameter extraction algorithms based on the Lorentzian or Gaussian profiles are easy to implement and the relative algorithm studies have now reached a certain maturity [ 20 , 21 ]. If the profiles are centered, the Voigt profile is a line profile resulting from the convolution of a Gaussian profile and a Lorentzian profile [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Key Parameter Extraction for Fiber Brillouin Distributed Sensors Based on the Exact Model

Zhi-niu

Zhao

2018

Sensors

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Errors in the extracted key parameters directly influence the errors in the temperature and strain measured by fiber Brillouin distributed sensors. Existing key parameter extraction algorithms for Brillouin gain spectra are mainly based on simplified models, therefore, the extracted parameters may have significant errors. To ensure high accuracy in the extracted key parameters in different cases, and consequently to measure temperature and strain with high accuracy, a key parameter extraction algorithm based on the exact Voigt profile is proposed. The objective function is proposed using the least-squares method. The Levenberg-Marquardt algorithm is used to minimize the objective function and consequently extract the key parameters. The optimization process is presented in detail, at the same time the initial values obtainment method and the convergence criterion are given. The influences of the number of sample points in Gauss-Hermite quadrature on the accuracy and the computation time of the algorithm are investigated and a suggestion about the selection of the number of sample points is given. The direct algorithm, the random algorithm and the proposed algorithm are implemented in Matlab and are used to extract key parameters for abundant numerically generated and measured Brillouin gain spectral signals. The results reveal that the direct algorithm requires less computation time, but its errors are considerably larger than that of the proposed algorithm. The convergence rate of the random algorithm is about 80~90%. The proposed algorithm can converge in all cases. Even for the convergence cases, the computation time and the fitting error of the random algorithm are 1~2 times larger than those of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

Key Parameter Extraction for Fiber Brillouin Distributed Sensors Based on the Exact Model

Zhi-niu

Zhao

2018

Sensors

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A fast key parameter extraction algorithm for long fiber distributed sensing based on Brillouin scattering

Zhao

Zhi-niu

et al. 2019

Review of Scientific Instruments

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A fast key parameter extraction algorithm is proposed to improve the real-time performance of temperature and strain measurements when performing Brillouin scattering-based fiber-distributed sensing. The algorithm uses a new initial value method that takes the extracted key parameters of the current point in the fiber as the initial guesses for the next point. Based on the old and new initial value method, the existing objective method, optimization algorithm, and convergence criterion, the key parameter extraction algorithms developed are implemented in Matlab using the typical Lorentzian, Gaussian, and pseudo-Voigt profiles. These algorithms are used to extract the parameters over a large range of measured Brillouin spectra for the entire fiber with different averaging times. The results reveal that apart from the case when the frequency sweep spans is less than the linewidth and the pseudo-Voigt profile is used (in this case, the mean computation time of the proposed algorithm is 1.1% larger than that of the referenced algorithm), the proposed algorithm not only ensures high accuracy in extracting the key parameters, but also improves the arithmetic efficiency by 16.3%–49.1%.

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Optimal frequency scanning range for parameters extraction from Brillouin scattering spectrum

Cited by 2 publications

References 14 publications

Key Parameter Extraction for Fiber Brillouin Distributed Sensors Based on the Exact Model

Key Parameter Extraction for Fiber Brillouin Distributed Sensors Based on the Exact Model

A fast key parameter extraction algorithm for long fiber distributed sensing based on Brillouin scattering

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