| 光谱学与光谱分析 |
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| Component Analysis of the Circulating Fluid in an Adsorption Tower in a P-Xylene Unit Based on Raman Spectral Decomposition |
| WANG Bin, DAI Lian-kui* |
| State Key Lab of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China |
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Abstract In order to achieve fast and accurate online analysis of the circulating fluid in an adsorption tower in a p-xylene unit, the Raman spectral analysis method is adopted. However, the Raman spectra of the pure components included in the circulating fluid overlap together, and the concentration of each component varies obviously, the present Raman analysis technology needs a large amount of training samples. Therefore, this paper applies Raman spectral decomposition method in component analysis of the circulating fluid. First of all, the Raman spectra of the pure components and the spectra of a few training samples must be measured, and baseline subtraction and mean normalization are applied to obtain pretreated Raman spectra. Then the characteristic wave number range, 680～880cm-1, is chosen, and the Raman spectral decomposition method is adopted, to get decomposition coefficients of each component for each training sample. Next, the mathematical model between coefficients and concentrations of each component are built based on all training samples. For a testing sample, the above spectral pretreatment and the spectral decomposition for the same wave number range is adopted, then the decomposition coefficients of each component can be obtained. Based on the built mathematical model, the concentrations of all components can be predicted. Experimental results show that the standard prediction errors for the concentration of toluene, ethylbenzene, p-xylene, m-xylene, o-xylene and p-diethylbenzene are 0.301%, 0.088%, 0.563%，0.384%, 0.366% and 0.536% respectively. The above method provides a methodological basis for the online analysis of the circulating fluid in adsorption towers.
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Received: 2013-11-28
Accepted: 2014-02-05
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Corresponding Authors:
DAI Lian-kui
E-mail: lkdai@iipc.zju.edu.cn
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