The Identification of the Mineral Oil Fluorescence Spectroscopy Based on the PCA and SVM

It has a great variety of the mineral oil. The composed of it with aromatic hydrocarbons structure is very often complicated, which caused the three-dimensional fluorescence spectroscopy of the different oil are various. The characteristic of the oil style-book are difficult to be maintained by the simple formula when the three-dimensional fluorescence spectroscopy technology is used to identify the species of the mineral oil. In this paper, the PCA is used to reduce the dimensions of the spectroscopy. The main feature of the spectroscopy is extracted by principal component analysis (PCA). The support vector machine(SVM) is used to assort the main characteristic root books which are abstracted by the PCA. The species identification of the mineral oil will be realized by it. The identification result is visualized by the parallel coordinate´s graph. The experiment results show that it is effective to reduce the dimensions of the spectroscopy and it preserved the usable information. The classify speed is greatly increased. The discrimination is 98%. It can effectively realize the identification of the oils.