|Table of Contents|

Research on the Fitting Algorithm of Multi-peakBrillouin Scattering Spectrum(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2019年01期
Page:
90-
Research Field:
·人工智能算法与应用专栏·
Publishing date:

Info

Title:
Research on the Fitting Algorithm of Multi-peakBrillouin Scattering Spectrum
Author(s):
Gao Yuan1; Gao Jianjun1; Du Jiahao1; Kong Weibin1; 2; 3; Wang Rugang1; 3; Zhou Feng1; 3
(1.School of Information Technology,Yancheng Institute of Technology,Yancheng 224051,China)(2.State Key Laboratory of Millimeter Waves,Southeast University,Nanjing 210096,China)(3.Yancheng Optical Fiber Sensing and Application Engineering Technology Res
Keywords:
multi-peak Brillouin scattering spectrum; RBF neural network; K-means clustering method; curve fitting
PACS:
TN248.1
DOI:
10.3969/j.issn.1001-4616.2019.01.014
Abstract:
In order to solve the problem that simultaneous detection of temperature and strain in optical fiber sensing technology cannot be accurately obtained by using fiber multi-peak Brillouin scattering spectrum,the RBF neural network based on K-means clustering method is applied to the data fitting of optical fiber multi-peak Brillouin scattering spectrum. Firstly,the theoretical knowledge of Radial Basis Function(RBF)Neural Network and K-means clustering method is described. Secondly,it is concluded that different diffusion speeds will affect the fitting accuracy of the data by using RBF neural network algorithm to fit the data. However,the smoothness and accuracy of fitting curves cannot be guaranteed simultaneously. The RBF neural network based on K-means clustering method is used to fit the data and get more accurate fitting curve,and the mean square error is small.

References:

[1] LIU J X,WANG M G,TANG Y,et al. Switchable optoelectronic oscillator using an FM-PS-FBG for strain and temperature sensing[J]. IEEE photonics technology letters,2017,29(23):2008-2011.
[2]WANG Y P,WANG M,XIA W,et al. Optical fiber Bragg grating pressure sensor based on dual-frequency optoelectronic oscillator[J]. IEEE photonics technology letters,2017,29(21):1864-1867.
[3]JIN X F,ZHU Y H,GUO J J,et al. Highly sensitive demodulation of a vibration-induced phase shift based on a low-noise OEO[J]. Optics letters,2017,42(20):4052-4054.
[4]YAO J P. Optoelectronic oscillators for high speed and high resolution optical sensing[J]. Journal of lightwave technology,2017,35(16):3489-3497.
[5]YIN B,WANG M G,WU S H,et al. High sensitivity axial strain and temperature sensor based on dual-frequency optoelectronic oscillator using PMFBG fabry-perot filter[J]. Optics express,2017,25(13):14106-14113.
[6]XU O,ZHANG J J,DENG H,et al. Dual-frequency optoelectronic oscillator for thermal-insensitive interrogation of a FBG strain sensor[J]. IEEE photonics technology letters,2017,29(4):357-360.
[7]董玉明,张旭苹,路元刚,等. 布里渊散射光纤传感器的交叉敏感问题[J]. 光学学报,2007,27(2):197-201.
[8]孙世林,周会娟,孟洲. 光纤布里渊分布式温度应变同时传感研究进展[J]. 半导体光电,2013,34(1):6-11.
[9]梁浩,张旭苹,李新华,等. 布里渊背向散射光谱数据拟合算法设计与实现[J]. 光子学报,2009,38(4):875-879.
[10]肖尚辉,李立. 一种新的光纤布里渊传感散射谱拟合方法[J]. 光学技术,2009,35(6):897-904.
[11]吕健刚,韦春桃. 基于BOTDA布里渊背向散射光谱数据的拟合算法[J]. 光学技术,2015,41(4):380-384.
[12]ZHAO L J,XU Z N,LI Y Q. An accurate and rapid method for extracting parameters from multi-peak Brillouin scattering spectra[J]. Sensors & actuators a physical,2015,232:276-284.
[13]张旭苹,张益听,王峰,等. 相位敏感型光时域反射传感系统光学背景噪声的产生机理及其抑制方法[J]. 物理学报,2017,66(7):73-86.
[14]丁硕,胡庆功,常晓恒,等. 基于LMBP神经网络的涡流传感器曲线拟合研究[J]. 信息技术,2013(1):17-21.
[15]郝海霞. 用粒子群算法优化BP神经网络进行函数拟合[J]. 山西师范大学学报(自然科学版),2017,30(1):14-16.
[16]张龙,杨长业,王晓蕾,等. 电容式降雨传感器及其特性曲线拟合方法[J]. 传感器与微系统,2017,36(10):27-30.
[17]樊高辉,刘尚合,魏明,等. 基于神经网络曲线拟合的电晕电流数学模型研究[J]. 高电压技术,2015,41(3):1034-1041.
[18]冯守良. 基于RBF网络曲线拟合的研究[J]. 黑龙江工程学院学报,2015,29(1):23-26.
[19]贾桂文,张景川,陈德旺,等. 基于BIC准则模型选择的光纤光栅波长温度拟合研究[J]. 传感技术学报,2014,27(2):217-219.
[20]董雄风,刘新学,王大彤,等. 基于神经网络的弹道曲线快速拟合方法[J]. 弹箭与制导学报,2014,34(2):135-138.

Memo

Memo:
-
Last Update: 2019-03-30