结合小波变换和经验模态分解的拉曼信号去噪研究
发布时间：2018-12-21 11:25
【摘要】：在分布式光纤温度传感器(DTS)的系统分析中,所探测到的含有温度信息的后向拉曼散射信号的强度十分微弱,并且所携带的噪声很大,严重影响了测温精度。针对该系统存在的噪声,提出了将小波变换和经验模态分解(EMD)相结合的方法对拉曼信号进行信号处理。实验结果表明:该方法能够有效地去除系统中的噪声,很好地保留了信号的有用部分,系统的信噪比由原来的5.7dB提高到15dB,系统的平均测温误差也由原来的2.8℃降到0.5℃,从而得到更加精确的温度值。
[Abstract]:In the system analysis of distributed optical fiber temperature sensor (DTS), the intensity of Raman scattering signal with temperature information is very weak, and the noise is very large, which seriously affects the precision of temperature measurement. Aiming at the noise existing in the system, a method combining wavelet transform with empirical mode decomposition (EMD) is proposed to process the Raman signal. The experimental results show that the proposed method can effectively remove the noise in the system and preserve the useful part of the signal. The signal-to-noise ratio of the system is improved from the original 5.7dB to 15 dB. The average temperature measurement error of the system is also reduced from 2.8 鈩，
本文编号：2388848
[Abstract]:In the system analysis of distributed optical fiber temperature sensor (DTS), the intensity of Raman scattering signal with temperature information is very weak, and the noise is very large, which seriously affects the precision of temperature measurement. Aiming at the noise existing in the system, a method combining wavelet transform with empirical mode decomposition (EMD) is proposed to process the Raman signal. The experimental results show that the proposed method can effectively remove the noise in the system and preserve the useful part of the signal. The signal-to-noise ratio of the system is improved from the original 5.7dB to 15 dB. The average temperature measurement error of the system is also reduced from 2.8 鈩，
本文编号：2388848
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