摘要
针对在分布式拉曼光纤温度传感器系统中,由于拉曼散射信号弱、噪声强而造成的温度测量误差问题,提出了一种改进小波算法模型。该算法在传统模型极大值小波算法基础上,引入信号相关性特性来提升捕捉信号与噪声的能力,同时结合小波分解尺度自适应方法,消除分解尺度不匹配造成信号丢失或噪声未滤除的情况,并在Matlab仿真软件中对比了此算法滤波的优越性,利用3 km分布式光纤测温系统进行验证。实验结果表明,处理后的温度较算法前的温度总体平均误差缩小0.5233℃。
In order to solve the problem of temperature measurement error caused by weak Raman scattering signal and strong noise in distributed Raman fiber temperature sensor,a improved wavelet algorithm model is presented.On the basis of the traditional modulus maxima wavelet algorithm,signal correlation is introduced to improve the ability of capturing signals and noise.Meanwhile,combined with wavelet decomposition scale adaptive method signal loss or noise unfiltering caused by decomposition scale mismatch is solved.The superiority of the filtering algorithm is compared with others by Matlab.The 3 km distributed optical fiber temperature sensing system is used for verification.Experimental results show that temperature error after the algorithm is generally reduced by 0.5233℃.
作者
綦慧
唐文娟
QI Hui;TANG Wen-juan(Information Department,Beijing University of Technology,Beijing 100124,China)
出处
《测控技术》
2019年第2期93-97,共5页
Measurement & Control Technology
关键词
光纤传感
温度
去噪
模极大值
相关性
尺度分解
fiber optical sensor
temperature
denoising
modulus maximum
relevance
scale decomposition
