摘要
基于布里渊散射的分布式光纤传感中温度和应变与布里渊频移成线性关系,为了提高温度和应变测量的准确性,提出了一种改进的二次多项式拟合算法用于提取布里渊频移。该算法分为两步:首先使用一种改进的中值滤波算法对含噪布里渊谱信号进行预处理,以提高增益峰值定位的准确性;然后截取围绕峰值左右对称的一个线宽的原始布里渊谱进行二次多项式拟合以实现布里渊频移的高精度提取。以布里渊频移误差及峰值定位准确性作为衡量指标,比较研究后确定同一频率下所有空间点对应的布里渊增益作为滤波器的输入。研究了不同扫频间隔和信噪比及不同滤波窗长下改进算法的效果,同时研究了最优窗长的选择问题。结果表明,不同信噪比和扫频间隔下改进算法均能有效提高布里渊频移提取的准确性。随窗口长度增加布里渊频移误差先减少后增加,在扫频间隔为1~10 MHz、信噪比为0~40 dB情况下,通用的最优窗长为53~163。
In distributed optical fiber sensing based on Brillouin scattering,Brillouin frequency shift(BFS)is linear to temperature and stain in the optical fiber.In order to improve the measurement accuracy of temperature and strain,an improved quadratic polynomial fitting algorithm is proposed.In the algorithm,the median filtering algorithm was proposed to preprocess the noisy Brillouin spectra,so as to improve the accuracy of gain peak location;then spectra within one linewidth and symmetrical about the peak gain were intercepted to extract the BFS precisely using the quadratic polynomial fitting algorithm.Firstly,after systematic comparison according to BFS error and error in frequency corresponding to peak value gain,the Brillouin gain of the same frequency corresponding to all spatial points was selected as the input signal.Subsequently,the effect of the proposed algorithm under different frequency intervals,signal to noise ratios(SNRs)and different filter window sizes was studied,meanwhile the optimal window size selection problem was investigated.The results show that the BFS error decreases first and then increases as the window size increases,and the general optimal window size ranges from 53 to 163.
作者
徐志钮
樊明月
赵丽娟
胡宇航
XU Zhiniu;FAN Mingyue;ZHAO Lijuan;HU Yuhang(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,CHN)
出处
《半导体光电》
CAS
北大核心
2020年第3期406-413,共8页
Semiconductor Optoelectronics
基金
国家自然科学基金项目(51607066,61775057)
河北省自然科学基金项目(E2019502177)
中央高校基本科研业务费专项资金项目(2020YJ005,2019MS090,2019MS085).
关键词
光纤分布式传感
布里渊频移
二次多项式拟合
中值滤波
去噪
distributed optical fiber sensing
Brillouin frequency shift
quadratic polynomial fitting
median filtering
denoise
