甲醇汽油是一种清洁能源, 甲醇汽油中甲醇的含量决定了汽油的性能。 通过中红外光谱对甲醇汽油中甲醇含量进行定量检测和分析。 首先, 对采集的甲醇汽油原始中红外光谱进行平滑处理(smoothing) 、 多元散射校正(MSC) 、 基线校正(baseline) 、 归一化(normalization) 等预处理, 再建立PLS模型, 对比选择最佳预处理方法, 结果表明: 在多元散射校正(MSC) 处理后建立的PLS模型效果最好, 模型的预测集相关系数r为0.918, 预测均方根误差RMSEP为2.107。 为进一步简化模型, 提高预测精度, 采用无信息变量消除(uninformative variable elimination, UVE)方法对波长进行筛选, 将UVE波段筛选之后的作为模型的输入变量, 采用偏最小二乘法(partial least squares, PLS) 、 主成分回归(principal components regression, PCR)和最小二乘支持向量机(least square support vector machine, LSSVM) 三种方法分别建立甲醇汽油中甲醇含量的定量预测模型, 并比较不同模型的预测效果和结果。 结果表明, 使用无信息变量消除可以较好提高数据的运算速度, 其中, UVE-PLS模型建模效果最好, r和RMSEP分别为0.923和2.075。 该实验表明中红外光谱检测甲醇汽油中甲醇含量是可行的并可以得到较好的效果; UVE是一种对甲醇汽油的中红外光谱非常有效的波段筛选方法, 该模型的建立对石油化工领域具有较为重要的意义。

Methanol gasoline is a new type of environmentally friendly diesel fuel, and the performance and quality of methanol-gasoline are based on the diesel methanol content. In this work, mid-infrared spectroscopy was successfully used to evaluate the methanol contents in methanol-gasoline samples with the aid of chemometric approaches. First, the mid-infrared spectral data obtained were pre-processed by smoothing standard normal, multiple scatter correction (MSC), baseline correction and normalization, and the partial least-square (PLS) quantitative calibration models were established, and the best pre-processed method was found. It was found that the PLS model pre-processed by MSC was much better than others, and the r and RMSEP evaluated were 0.918 and 2.107, respectively. In order to simplify the model and improve the prediction accuracy, uninformative variable elimination (UVE) was used to select the optimal wavelengths, and the experimental results showed that the prediction ability was greatly improved. Different quantitative calibration models by UVE selected wavelength, such as partial least-square (PLS), principal component regression (PCR) and least square-support vector machine (LS-SVM) for measuring methanol content were established and their prediction results were compared. It was found that the UVE-PLS model was much better than others, and the r and RMSEP evaluated were 0.923 and 2.075. It suggested that infrared spectroscopy in the detection of methanol content in the methanol gasoline is feasible and can bring good prediction results. UVE is an effective method for methanol gasoline in the infrared spectrum of band selection method, which is significant for the development of oil chemical industry.