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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摘要基于光纤拉曼散射效应和Monte-Carlo法,建立了一种DTS传感模型。采用非线性遗传算法对该模型的参数进行了辨识,分析了种群规模、进化代数、交叉率、变异率等参数选值对算法运行结果的影响,并选取了最佳参数组合。搭建了分布式光纤温度传感系统实验平台,并运用该DTS传感模型对分布式光纤温度传感系统进行了仿真预测。实验及仿真结果表明:该传感模型在空间分辨力为1 m时,预测误差在0.24%以内;该分布式光纤温度传感系统的测温误差不大于0.40 ℃。

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	滕峰成
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关键词 ：计量学, 分布式光纤温度传感系统, 非线性遗传算法, 参数辨识, 测温误差

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

收稿日期: 2018-03-26 发布日期: 2019-06-10

PACS:

TB942

通讯作者: 滕峰成 E-mail: tengfengcheng@126.com

作者简介: 滕峰成(1966-),男,河北沧州人,燕山大学副教授,主要研究方向为光电传感技术。Email: tengfengcheng@163.com

引用本文:

滕峰成,张昊阳,程安迪,王珊珊. 基于非线性遗传算法的DTS传感模型的参数辨识与优化[J]. 计量学报, 2019, 40(4): 610-617.
TENG Feng-cheng,ZHANG Hao-yang,CHENG An-di,WANG Shan-shan. Parameter Identification and Optimization of the DTS Sensing Model Based on the Nonlinear Genetic Algorithm. Acta Metrologica Sinica, 2019, 40(4): 610-617.

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

［1］Zu P, Chan C C, Lew W S, et al. Magneto-optical fiber sensor based on magnetic fluid［J］. Optics letters, 2012, 37(3): 398-400.
［2］Adachi S. Distributed optical fiber sensors and their applications［C］// IEEE Proceedings of the SICE Annual Conference. Tokyo, Japan, 2008: 329-333.
［3］李永倩, 赵丽娟, 杨志, 等. 基于BOTDR的海缆3D立体监测系统设计与实现［J］. 仪器仪表学报, 2014, 35(5): 1029-1036.
Li Y Q, Zhao L J, Yang Z, et al. Design and realization of the submarine cable three-dimensional monitoring system based on BOTDR［J］. Chinese Journal of Scientific Instrument, 2014, 35(5): 1029-1036.
［4］朱丹丹,李伟欣,李志全,等. 分布式光纤光栅应变和温度同时测量系统［J］. 计量学报, 2008, 29(1): 31-34.
Zhu D D, Li W X, Li Z Q, et al. A Distributed Fiber Bragg Grating System Simultaneously Measuring the Strain and Temperature［J］. Acta Metrologica Sinica, 2008, 29(1): 31-34.
［5］张勇, 魏广庆, 施斌, 等. 基于BOTDR的传感光纤温度效应研究［J］. 电子测量与仪器学报, 2010, 24(10): 929-934.
Zhang Y, Wei G Q, Shi B, et al. Study on temperature effect of BOTDR-based optical fibers［J］. Journal of Electronic Measurement and Instrument, 2010, 24(10): 929-934.
［6］Tu G J, Zhang X P, Zhang Y X, et al. The development of an Φ-OTDR system for quantitative vibration measurement［J］. IEEE Photonics Technology Letters, 2015, 27(12): 1349-1352.
［7］盛健, 张在宣, 王剑锋, 等. 30公里远程分布式光纤拉曼温度传感器系统测试方法与技术的研究［J］. 计量技术, 2004, (2): 16-19.
Sheng J, Zhang Z X, Wang J F, et al. Study on test method and technology of 30km remote distributed fiber Raman temperature sensor system［J］. Measurement Technique, 2004, (2): 16-19.
［8］毕卫红, 杨希鹏, 李敬阳, 等. 布里渊光时域反射系统中布里渊散射信号的前向和后向拉曼放大研究［J］. 中国激光, 2014, 41(12): 142-147.
Bi W H, Yang X P, Li J Y, et al. Forward and backward Raman amplification of Brillouin scattering signal in Brillouin optical time domain reflectometer system［J］. Chinese Journal of Lasers, 2014, 41(12): 142-147.
［9］张在宣, 郭宁, 余向东, 等. 分布式光纤传感温度报警系统［J］. 计量技术, 2000, (2): 24-26.
Zhang Z X, Guo N, Yu X D, et al. Distributed optical fiber sensing temperature alarm system［J］. Measurement Technique, 2000, (2): 24-26.
［10］Qin Z G, Chen L, Bao X Y. Wavelet denoising method for improving detection performance of distributed vibration sensor ［J］. IEEE Photonics Technology Letters, 2012, 24(7): 542-544.
［11］Yilmaz G, Karlik S E. A distributed optical fiber sensor for temperature detection in power cables ［J］. Sensors and Actuators A: Physical, 2006, 125(2): 148-155.
［12］王剑锋, 刘红林, 张淑琴, 等. 基于拉曼光谱散射的新型分布式光纤温度传感器及应用［J］. 光谱学与光谱分析, 2017, 33(4): 865-871.
Wang J F, Liu H L, Zhang S Q, et al. New type distributed optical fiber temperature sensor (DTS) based on Raman scattering and its application［J］. Spectroscopy and Spectral Analysis, 2013, 33(4): 865-871.
［13］杨睿, 李小彦, 高翔. 一种修正分布式拉曼光纤测温系统测量误差的方法［J］. 光子学报, 2015, 44(10): 104-109.
Yang R, Li X Y, Gao X. A method to correct measurement error of distributed Raman optical fiber temperature measurement system［J］. Acta Photonica Sinica, 2015, 44(10): 104-109.
［14］张在宣, 金尚忠, 王剑锋, 等.分布式光纤拉曼光子温度传感器的研究进展［J］. 中国激光, 2010, 37(11): 2749-2761.
Zhang Z X, Jin S Z, Wang J F, et al. Distributed optical fiber Raman photon sensor research review［J］. Chinese Journal of Lasers, 2010, 37(11): 2749-2761.
［15］滕峰成, 林晓乐, 郝宇, 等. 基于非线性GA算法的MFF透射模型的参数辨识与优化［J］. 仪器仪表学报, 2016, 37(2): 286-293.
Teng F C, Lin X L, Hao Y, et al. Parameter identification and optimization of MFF transmission model based on nonlinear genetic algorithm［J］. Chinese Journal of Scientific Instrument, 2016, 37(2): 286-293.
［16］滕峰成, 林晓乐, 张崇兴, 等. 基于非线性GA算法的动态P模型的参数辨识与验证［J］. 仪器仪表学报, 2015, 36(5): 1123-1130.
Teng F C, Lin X L, Zhang C X, et al. Parameter identification and verification of dynamic P model based on nonlinear genetic algorithm［J］. Chinese Journal of Scientific Instrument, 2015, 36(5): 1123-1130.