摘要
应用便携式拉曼光谱仪测量了汽油样本的拉曼光谱,以自适应迭代惩罚最小二乘方法(airPLS)对光谱进行了背景扣除和平滑处理,并选取特征峰区间利用偏最小二乘方法(PLS)建立了预测甲基叔丁基醚(MT-BE)的校正模型。以训练集相关系数和拟合误差及测试集相关系数和预测误差作为判定依据,确定了最佳建模条件。最终训练集相关系数为0.996 0,拟合误差为0.316 1,测试集相关系数为0.996 6,预测误差为0.490 1。结果表明采用便携式拉曼光谱结合化学计量学方法处理,可以满足对汽油中MTBE含量快速检测的要求。
Raman spectroscopy as a rapid,non-destructively testing technique has been widely used in many fields.In this study,49 spectra of gasoline samples were collected with portable Raman spectrometer.Adaptive iteratively reweighted penalized least squares was employed to remove the strong fluorescence background of the spectra.The partial least squares（PLS） calibration model was established in the optimal conditions to predict the content of MTBE.Correlation coefficient,fitting error of training set samples and correlation coefficient,prediction error of test set samples were used to evaluate the quality of the model.The best model showed the satisfactory predictions for the four values mentioned above：0.996 0,0.316 1 and 0.996 6,0.490 1.The results showed that the method was suitable for the fast and reliable determination of the MTBE in gasoline.
出处
《分析测试学报》
CAS
CSCD
北大核心
2012年第5期541-545,共5页
Journal of Instrumental Analysis
