基于非线性遗传算法的DTS传感模型的参数辨识与优化

doi:10.3969/j.issn.1000-1158.2019.04.11

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Abstract Based on fiber Raman scattering efficiency and Monte-Carlo method, a DTS sensing model is established. The nonlinear genetic algorithm is adopted to conduct the parameters identification of DTS sensing model, and the influence of the population size, evolutionary algebra, crossover rate and mutation rate on the operation result of the algorithm are analyzed,and the optimal parameter combination is selected. The experimental platform of distributed optical fiber temperature sensing system is established, and the DTS sensing model is used to conduct the simulation predicted of distributed optical fiber temperature sensing system. The results of the experiment and simulation show that the predictive error of the sensing model is within 0.24% when the spatial resolution is 1 m, and the temperature measurement error of the distributed optical fiber temperature sensing system is no more than 0.40 ℃.

Key words： metrology DTS sensing model;nonlinear genetic algorithm;parameter identification temperature measurement error

Received: 26 March 2018 Published: 10 June 2019

PACS:

TB942

Corresponding Authors: Feng-Cheng Teng E-mail: tengfengcheng@126.com

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	TENG Feng-cheng
	ZHANG Hao-yang
	CHENG An-di
	WANG Shan-shan

Cite this article:

TENG Feng-cheng,ZHANG Hao-yang,CHENG An-di, et al. Parameter Identification and Optimization of the DTS Sensing Model Based on the Nonlinear Genetic Algorithm[J]. Acta Metrologica Sinica, 2019, 40(4): 610-617.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2019.04.11 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2019/V40/I4/610

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