近红外光谱分析技术在油品质量分析中的应用

Application of Near Infrared Spectroscopy in Oil Quality Analysis

分析了近红外光谱在油品质量分析中应用的工作原理 ,介绍了常用的几种近红外光谱定量、定性分析方法 .定量分析方法主要有多元线性回归 (MLR)、主成分回归 (PCR)、偏最小二乘法 (PLS)与人工神经网络法 (ANN)等 ;定性分析方法包括峰位鉴别法、模式识别法等 ,并对这几种方法进行了比较 .进一步介绍了近红外光谱技术在柴油、汽油等油品质量分析中的应用成果 .结果表明 ,近红外光谱分析技术是分析油品质量的一种有效而便利的方法 。

The article analyzed the working theory in the application of near infrared spectrum and briefly discussed several common technologies in qualitative and quantitative analysis of near infrared spectroscopy. Quantitative analysis methods include multivariate linear regression, principal component regression, partial least squares method and artificial neural network etc ; qualitative analysis methods include NIR spectrum peak position identification, pattern recognition etc , and all these methods are compared. Moreover, the article introduced some achievements in application in gasoline, diesel oil quality analysis with near infrared spectroscopy. Near infrared spectroscopy methods are efficient and convenient for the application of analysis of oil quality, it has considerable applied value in industry.