基于神经网络的光纤温度和应变快速解调方法  

Fast demodulation method of optical fiber temperature and strain based on neural network

作　　者：王成亮[1] 杨庆胜 李军[1] 钟巍峰 陈志明[1] WANG Chengliang;YANG Qingsheng;LI Jun;ZHONG Weifeng;CHEN Zhiming(Jiangsu Frontier Electric Power Technology Co. Ltd., Nanjing 211103, China)

机构地区：[1]江苏方天电力技术有限公司,南京211103

出　　处：《激光技术》2022年第2期254-259,共6页Laser Technology

基　　金：江苏方天电力技术有限公司科技项目(KJ201917)。

摘　　要：为了提高基于布里渊散射的分布式光纤传感系统实时性,在分析经典基于洛伦兹和伪Voigt模型拟合法优缺点的基础上,将多层前馈神经网络方法用于布里渊频移的估算。确定了神经网络的结构、输入及输出量、激活函数和训练算法,采用不同信噪比(5dB~40dB)和布里渊频移(10.62GHz~10.82GHz)的布里渊谱训练该网络,训练完成后网络针对训练样本的布里渊频移预测误差仅约为1MHz,同时也训练了径向基函数神经网络。针对温度和应变沿线波动的布里渊谱分别采用以上训练得到的多层前馈神经网络、径向基函数神经网络、基于洛伦兹模型的谱拟合法和基于伪Voigt模型的谱拟合法估算光纤沿线的布里渊频移并解调获得光纤沿线的温度和应变。结果表明,多层前馈神经网络方法的准确性与经典的基于洛伦兹模型和伪Voigt模型的谱拟合法相似,但计算时间仅为后两者的1/947.16~1/470.95和1/784.56~1/532.88。该研究为基于布里渊散射的光纤温度和应变快速测量提供了参考。To improve the real-time performance of distributed optical fiber sensing system based on Brillouin scattering,through the analysis of the strengths and weaknesses of the classical Lorentzian and pseudo-Voigt models fitting methods,the multi-layer feedforward artificial neural network(ANN)method was used to estimate the Brillouin frequency shift.The structure,input and output,activation function,and training algorithm of the ANN were determined.The ANN was trained by simulated Brillouin spectra with different signal-to-noise ratios(5dB~40dB)and Brillouin frequency shifts(10.62GHz~10.82GHz).The Brillouin frequency shift estimation error of the trained ANN for the training samples was only about 1MHz.At the same time,the radial basis function ANN was also trained.For the Brillouin spectra with temperature and strain varied along the optical fiber,the trained multi-layer feedforward ANN and radial basis function ANN,the spectrum fitting methods based on the Lorentzian model and the pseudo-Voigt model were respectively used to estimate the Brillouin frequency shift along the optical fiber,and at the same time the temperature and strain along the optical fiber were obtained by demodulation.The results show that the accuracy of the multi-layer feedforward ANN method is similar to that of the classical spectral fitting method based on the Lorentzian and pseudo-Voigt models,but the calculation time is only 1/947.16~1/470.95 and 1/784.56~1/532.88 of the latter two.This work provides a reference for the rapid measurement of optical fiber temperature and strain based on Brillouin scattering.

关 键 词：传感器技术 温度和应变 神经网络 解调 快速 

分 类 号：TN247[电子电信—物理电子学]