改进小波算法在光纤温度传感器中的应用
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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 ℃.
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 ℃.
引文
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[2] Hartog A. A distributed temperature sensor based on liquidcore optical fibers[J]. Lightwave Technology, 1983,1(3):498-509.
[3]田兵.矿用分布式光纤测温系统软件设计与实现[J].中州煤炭,2016(8):105-109.
[4]曹进军,朱宽,郝亚飞,等.露天煤矿高温火区爆破测温技术的研究与应用[J].爆破,2016,33(2):128-131.
[5]张纯玺.光纤光栅温度监测系统设计及其在高低压开关柜中的应用[D].济南:山东大学,2010.
[6]李成榕,马国明.光纤布喇格光栅传感器应用于电气设备监测的研究进展[J].中国电机工程学报,2013,33(12):114-122.
[7]廖志军,黄新波,赵阳,等.基于光纤光栅的高压开关柜温度监测系统设计[J].广东电力,2015(3):50-55.
[8]周娜.基于准分布式光纤测温技术的GIS母线触点温度在线监测系统的研究[D].保定:华北电力大学,2014.
[9]赵健,朱莎露,潘建宇,等.分布式光纤温度传感器在油库中的应用[J].光通信技术,2015,39(4).
[10]刘敏敏,周峰,杜志顺.光纤传感器在石油测井中的应用[J].光学与光电技术,2008,6(3):18-21.
[11]邢晨辉.基于光纤传感系统的石油测井技术进展[J].中国石油和化工标准与质量,2014,34(3):146.
[12]王瑾,吕永健,赵永安.光纤温度传感器在航空测控中的应用[J].传感器与微系统,2002,21(11):55-56.
[13]刘铁根,王双,江俊峰,等.航空航天光纤传感技术研究进展[J].仪器仪表学报,2014(8):1681-1692.
[14] Leandio D,Ullan A,Loayssa A,et al. Remote(155 km)fiber bragg grating interrogation technique combining Raman,Brillouin,and Erbium gain in a fiber laser[J]. IEEE Photonics Technology Letters,2011,23(10):621-623.
[15] Wu H,Wang M,Liu T Q,et al. Few mode fibers based quasi-single mode Raman distributed temperature sensor[C]//2017 25 th Optical Fiber Sensors Conference. 2017.
[16]陈珂.光纤IOFDR分布温度传感及多传感器融合技术研究[D].大连:大连理工大学,2015.
[17]王剑锋,刘红林,张淑琴,等.基于拉曼光谱散射的新型分布式光纤温度传感器及应用[J].光谱学与光谱分析,2013,33(4):865-871.
[18]孙柏宁.分布式拉曼光纤温度传感系统的噪声分析及优化[D].济南:山东大学,2014.
[19]沈小青,杨洋,王志虎,等.光纤测温系统实时性及分辨率优化与应用[J].半导体光电,2017,38(1):113-116.
[20]江虹,苏阳,李进,等.一种小波阈值去噪在FBG解调中的改进方法[J].光通信研究,2016(2):40-43.
[21]张正文.分布式光纤温度传感系统的设计及优化[D].淮南:安徽理工大学,2016.
[22]付勇.基于分布式光纤的电缆温度监测系统信号处理的研究[D].锦州:辽宁工业大学,2016.
[23]王慧,崔连延.基于LMS算法的分布式光纤测温系统中信号处理研究[J].电气自动化,2017,39(1):113-115.
[24]杜继永,黄国荣,程洪炳,等.基于改进小波阈值法处理MEMS陀螺信号噪声[J].电光与控制,2009,16(12):61-64.
[25]王宗良.分布式光纤拉曼温度传感系统信号处理及性能提升[D].济南:山东大学,2015.
[26] Hu D I,Zhao X H,Mu Z C,et al. Distinguish method of fatigue state based on driving behavior wavelet analysis[C]//Proceedings of the 32nd Chinese Control Conference. 2013:3590-3596.