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作 者:肖家悦 傅海威[1] 陈苗 李根 程嘉慧 XIAO Jiayue;FU Haiwei;CHEN Miao;LI Gen;CHENG Jiahui(Engineering Research Center of Shaanxi Province for Oil and Gas Resource Optical Fiber Detection/Key Laboratory of Shaanxi Province for Measurement and Control Technology of Oil and Gas Wells,Xi’an Shiyou University,Xi’an,Shaanxi 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陕西省油气井测控技术重点实验室,陕西西安710065
出 处:《西安石油大学学报(自然科学版)》2024年第3期137-142,共6页Journal of Xi’an Shiyou University(Natural Science Edition)
基 金:陕西省科技计划项目(2019GY-176);西安石油大学研究生创新基金资助项目(YCS22213186)。
摘 要:在分布式光纤拉曼温度传感系统中,反斯托克斯光包含了温度信息,但其强度相对较弱,易受到噪声干扰。传统的信号去噪方法往往会滤除系统所具有的原始特征。针对这一问题,本文提出了改进的小波阈值方法,将3sigm准则与传统算法相结合。在该算法中,对信号进行小波分解,再对分解的各层小波系数进行阈值处理,使用3sigm值来区分有用信号和噪声,然后进行小波重构,实现信号去噪。在7 km长的多模光纤上进行温度测量实验,使用改进的算法对数据进行分析。结果表明,改进的方法处理后的温度波动平均为0.991℃,相较于传统算法得到的2.422℃,提高了1.431℃。与传统算法相比,3sigm准则算法提高了测温精度,并为阈值的选择提供了新的思路,使阈值的选择更具统计意义。In a distributed fiber Raman temperature sensing system,anti Stokes light contains temperature information,but its intensity is relatively weak and susceptible to noise interference.Traditional signal denoising methods often filter out the original features of the system.An improved wavelet thresholding method was proposed to address this issue,combining the 3Sigm criterion with traditional algorithms.In this algorithm,the signal is subjected to wavelet decomposition,and then the threshold processing of all wavelet coefficients of decomposed layers are carried out.The useful signal and noise are distinguished using a 3 sigm value,and then wavelet reconstruction is performed to achieve signal denoising.The temperature measurement experiments on long multimode fiber of 7 km are conducted and the experimental data are analyzed using the improved algorithm.The results show that the average fluctuation of the processed temperature data by the improved method is 0.991℃,which is 0.888℃higher than the 2.422℃obtained by traditional algorithms.Compared with the traditional algorithms,the 3Sigm criterion algorithm improves temperature measurement accuracy and provides new ideas for the selection of threshold,making threshold selection more statistically significant.
分 类 号:TN253[电子电信—物理电子学] TE97[石油与天然气工程—石油机械设备]
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