基于Voigt峰的未知成分光谱拟合算法及其在甲醇汽油定量分析中的应用  

Raman Spectra of Unknown Components Fitting Algorithm Based on Voigt Function and Its Application in Methanol-Gasoline Quantitative Analysis

作　　者：李津蓉[1] 戴连奎[2] 武晓莉[1] 周扬[1] 

机构地区：[1]浙江科技学院自动化与电气工程学院,杭州310023 [2]浙江大学工业控制技术国家重点实验室,杭州310027

出　　处：《分析化学》2014年第10期1518-1523,共6页Chinese Journal of Analytical Chemistry

基　　金：浙江省自然科学基金项目(No.LQ14F050002);国家自然科学基金项目(No.61203371);浙江省教育厅科研计划项目(Y201327869)资助~~

摘　　要：提出了一种基于Voigt函数的未知成分拉曼光谱拟合算法，利用Voigt峰函数的叠加形式对样本中未知成分所产生的背景光谱进行拟合。在扣除背景光谱影响后，利用被测成分的光谱贡献权值与成分浓度之间建立线性关系模型。实验在3种成分不同的基础汽油中加入不同体积比例（2.5%～80.0%）的甲醇溶液，利用本方法对成分未知的基础汽油所产生的背景光谱进行拟合，扣除拟合光谱后，剩余光谱即可视为甲醇的光谱贡献。基于4个训练样本建立了甲醇光谱贡献权值与浓度之间的线性定量分析模型，模型的预测均方误差（RMSEP）为1.86%，复相关系数（R2）达到0.987。结果表明，此方法可有效解决混合物中光谱重叠问题，具有训练样本少、外推性强的优点。A Raman spectrum fitting method based on Voigt function was proposed. The method can be used to fit the profile of Raman spectrum produced by unknown components in sample based on Voigt functions. In the experiment, pure methanol was added by various volume fraction （ 2. 5% -80. 0%） into three base-gasoline with different compositions. It can be applied to fit the background Raman spectrum produced by basic-gasoline comprised of unknown compositions. The remained spectrum, after deducting the fitted spectrum from the mixture spectrum, was considered as the contribution attributed only to methanol. And then a linear calibration model was built based on 4 training samples to predict the concentration of methanol. The root mean square error of prediction （RMSEP） was 1. 86% （V/V） and the correlation coefficient （R2） was 0. 987. Results show that it is an effective method to solve the problem of strong spectral overlap in mixture, and it has the advantages of high generalization and few training samples.

关 键 词：拉曼光谱 未知成分 非线性变化 定量分析 

分 类 号：TE626.21[石油与天然气工程—油气加工工程] O657.3[理学—分析化学]