光谱学与光谱分析 |
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Denoising and Assessing Method of Additive Noise in the Ultraviolet Spectrum of SO2 in Flue Gas |
ZHOU Tao1, SUN Chang-ku1, LIU Bin1, ZHAO Yu-mei2 |
1. State Key Lab of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China 2. Tianjin Lanyu Technology Co., Ltd., Tianjin 300384, China |
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Abstract The problem of denoising and assessing method of the spectrum of SO2 in flue gas was studied based on DOAS. The denoising procedure of the additive noise in the spectrum was divided into two parts: reducing the additive noise and enhancing the useful signal. When obtaining the absorption feature of measured gas, a multi-resolution preprocessing method of original spectrum was adopted for denoising by DWT (discrete wavelet transform). The signal energy operators in different scales were used to choose the denoising threshold and separate the useful signal from the noise. On the other hand, because there was no sudden change in the spectra of flue gas in time series, the useful signal component was enhanced according to the signal time dependence. And the standard absorption cross section was used to build the ideal absorption spectrum with the measured gas temperature and pressure. This ideal spectrum was used as the desired signal instead of the original spectrum in the assessing method to modify the SNR (signal-noise ratio). There were two different environments to do the proof test-in the lab and at the scene. In the lab, SO2 was measured several times with the system using this method mentioned above. The average deviation was less than 1.5%, while the repeatability was less than 1%. And the short range experiment data were better than the large range. In the scene of a power plant whose concentration of flue gas had a large variation range, the maximum deviation of this method was 2.31% in the 18 groups of contrast data. The experimental results show that the denoising effect of the scene spectrum was better than that of the lab spectrum. This means that this method can improve the SNR of the spectrum effectively, which is seriously polluted by additive noise.
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Received: 2008-11-06
Accepted: 2009-02-08
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Corresponding Authors:
ZHOU Tao
E-mail: zhoutao_tom@hotmail.com
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