基于低分辨率色散型拉曼光谱仪的汽油苯含量快速分析

针对汽油苯含量的快速分析问题,提出了基于低分辨率色散型拉曼光谱仪的新的检测方法。由于色散型拉曼光谱中存在着严重的测量噪声和荧光背景干扰,应用多项式平滑滤波除噪声和迭代多项式拟合基线校正方法减少荧光背景的干扰。随后,分别采用岭回归、主成分回归、偏最小二乘回归方法,对炼油厂的汽油样本建立了三个苯含量的快速分析模型并对其进行验证。实验表明,基于低分辨率色散型拉曼光谱仪进行汽油苯含量分析,结合常规建模方法,重复性和再现性均满足SH/T0713—2002标准的要求,此外由于其具有低成本、小型易携带等优点,适用于日常快速分析。

Fast analysis of benzene concentration in gasoline based on low-resolution dispersive Raman spectroscopy

In order to fast analyze the benzene concentration in gasoline, a new measure method based on low-resolution dispersive Raman spectroscopy is proposed. There exist strong measurement noise and fluorescence background in dispersive Raman spectra, so the present paper applies the Savitzky-Golay smoothing filter to remove the measurement noise and uses iterative polynomial curve-fitting to reduce the fluorescence background. Based on ridge regression, principal component regression and partial least squares algorithm, three calibration models of the benzene concentration in gasoline are built and validated by a set of gasoline samples from a refinery. Experimental results show that their repeatability and reproducibility can satisfy the accuracy requirement specified by the standards SH/T0713-2002, regardless of applying what kind of calibration models. In addition to its low cost, small size, convenience to use and so on, the fast measure method based on low-resolution dispersive Raman spectroscopy can be widely applied to the routine analysis.