光学精密工程2017，Vol.25Issue(4)：884-890,7.DOI:10.3788/OPE.20172504.0884
基于PCA的时间分辨油荧光光谱分析及优化
Spectral analysis and optimization of time-resolved oil fluorescence based on PCA
摘要
Abstract
Laser-induced Fluorescence (LIF) technique can be widely used in oil pollution monitoring.However, ordinary oil fluorescence spectra can only achieve cursory oil classification, which was disabled to distinguish crude and fuel oils.Herein, time-resolved fluorescence spectra classification method based on Principle Component Analysis (PCA) was investigated and employed to analyze the spectral features of 20 kinds of oils, of which the fluorescence lifetimes and the spectral timing characteristics were obtained.Then referring to fluorescence lifetimes of oils (less than 10 ns commonly), three-dimensional spectra of samples within this time range were used for obtaining a vector space which was composed of first three principal components and was considered as a three-dimensional coordinate system.In this coordinate system, correlation distances of position vectors at difference delay time of fluorescence acquisition were analyzed for spectral clustering of time-resolved oil fluorescence.To reflect timing characteristics of correlation distances, dispersion parameters were introduced into the PCA optimization method.The experimental result indicates that the method based on time-resolved fluorescence spectroscopy can discriminate between crude oils and fuel oils with a higher recognition rate.关键词
时间分辨荧光光谱/油荧光分类/主成分分析(PCA)/荧光寿命Key words
time-resolved fluorescence spectrum/classification of oil fluorescence/Principal Component Analysis (PCA)/fluorescence lifetime分类
数理科学引用本文复制引用
李杰,李晓龙,唐秋华,赵朝方,王炯炯..基于PCA的时间分辨油荧光光谱分析及优化[J].光学精密工程,2017,25(4):884-890,7.基金项目
国家自然科学基金资助项目(No.61505221) （No.61505221）
国家海洋局国际海洋合作与履约项目(No.QY0516014) （No.QY0516014）
中央级公益性科研院所基本科研业务费专项资金资助项目(No.0215G20) （No.0215G20）
