基于SSA-SVR算法的光纤光栅波长解调方法  

FBG Wavelength Demodulation Method Based on Support Vector Regression Optimized by Sparrow Search Algorithm

作　　者：刘颖刚[1] 李飞[1] 袁宇博 李瑞[1] 周蕊 徐心怡 LIU Yinggang;LI Fei;YUAN Yubo;LI Rui;ZHOU Rui;XU Xinyi(Shaanxi Engineering Research Center of Oil and Gas Resource Optical Fiber Detection,Xi'an Shiyou University,Xi'an 710065,China)

机构地区：[1]西安石油大学陕西省油气资源光纤探测工程研究中心,西安710065

出　　处：《光子学报》2025年第1期18-28,共11页Acta Photonica Sinica

基　　金：陕西省重点科学研究计划项目(No.2020JS122);西安石油大学研究生创新与实践能力培养计划资助(No.YCS23213188)。

摘　　要：针对可调谐光纤法布里-珀罗滤波器在光纤光栅解调中受到迟滞和温漂特性影响导致解调误差增大的问题,提出一种基于麻雀搜索算法优化支持向量回归的光纤光栅波长解调方法。采用滑动窗口与支持向量回归结合的方法构建可调谐光纤法布里-珀罗滤波器的波长补偿模型。实验结果表明,当锯齿波调谐频率为0.5 Hz时,该模型补偿后的漂移波长平均绝对误差和均方误差分别降低至18.47 pm和1.21 pm。稳定性测试中,该方法解调波长值与sm125解调值之间的平均绝对误差为7.28 pm;40~90℃降温实验中,该解调方法的平均绝对误差为7.44 pm。此方法验证了光纤光栅解调系统在不借助硬件参考的情况下,可以有效降低光栅波长解调误差。Fiber Bragg grating(FBG)wavelength demodulation technique based on tunable Fabry-Perot(F-P)filters(FFP-TF)results in a degradation of the accuracy of the demodulation system due to the hysteresis and temperature drift characteristics of piezoelectric ceramics(PZT)inside the FFP-TF.Artificial intelligence machine learning algorithms can reduce the demodulation error of the system without increasing the complexity of the system.Therefore,this article proposes an FBG wavelength demodulation method based on Support Vector Regression(SVR)optimized by Sparrow Search Algorithm(SSA).The main purpose is to establish a nonlinear fitting relationship between F-P tuning voltage and transmission wavelength,replacing wavelength reference hardware.This method can save system costs,improve system demodulation accuracy,and contribute to the integrated development of demodulation systems.First,the reference grating,driving voltage,tuning time and F-P surface temperature are taken as the input features of the model,and the F-P transmission wavelength is taken as the output feature,and the F-P transmission wavelength compensation model is established by SVR.The SSA-optimized hyperparameters C and g are then input into the SVR model for training to obtain the target compensation model.Meanwhile,the training method of combining sliding window with SVR is proposed to improve the model's global optimization-seeking ability by updating the sliding window's size and sliding speed,which avoids the problem of the model's deterioration in generalization ability over time.After the model training,the correlation coefficient(R2),Mean Square Error(MSE),and Root Mean Square Error(RMSE)are introduced to evaluate the model and obtain the optimal compensation model.Finally,the FBG wavelength demodulation system based on SSA-SVR is built in Labview and the optimal training model is called.Then the real-time compensation ability of the model is checked by the stability experiment and the cooling experiment.The law of the wavelength compensation error

关 键 词：光纤光栅 波长解调 机器学习 可调谐法布里-珀罗滤波器 波长漂移补偿 

分 类 号：O436[机械工程—光学工程]