The Fluorescence Spectroscopy Recognition of the Mineral Oil Based on the ICA and the Wavelet Neural Network
The composed of the mineral oil with aromatic hydrocarbons structure is very often complicated,which caused the three-dimensional fluorescence spectroscopy of the different oil are al so similar and overlapped in a wide wavelength arrange.The eigenvectors are obtained by the Excitation-Emission Matrix (EEM) factorization from the three-dimensional fluorescence spectroscopy.The composed of it with aromatic hydrocarbons structure is very often complicated,which caused the threedimensional fluorescence spectroscopy of the different oil are various.The characteristic of the oil style-book are difficult to be maintained by the simple formula.In this paper,the independent component analysis (ICA) is used to do the matrix decomposition from the perspective of independence to extract the main feature of the spectroscopy.The mapping relation was obtained by the VVNN between the singular value eigenvector and the species of the mineral oil.The WNN realized the recognition of the different kinds of mineral oil.The experiment result indicates that the right of the distinguish rate is 91％.
ICA WNN fluorescence spectroscopy spectral recognition mineral oil
Song Aijuan Lv Jiangtao Ren Yuxin
Department of Automation Engineering,Northeastern University at Qinhuangdao,China Department of Automation Engineering,T1ANJIN Urban Construction Design.China
国际会议
秦皇岛
英文
112-114
2010-11-05（万方平台首次上网日期，不代表论文的发表时间）