摘要
为了达到快速识别和检测油类污染物的目的,以激光诱导荧光技术为基础搭建了荧光光谱检测系统,得到0^#柴油、95^#汽油和普通煤油3种不同油种的荧光光谱,然后从荧光光谱信息中提取特征参量,将标准差、中心距和荧光峰的峰度系数作为敏感特征参量进行聚类分析,最后采用拟合曲线法求得待测样品的质量浓度。实验结果表明,LIF技术结合特征参量提取法和拟合曲线法可用于不同油类污染物的定性和定量检测,为快速识别和检测油类污染物提供了一种新思路。
To realize the rapid identification and detection of oil pollutants,a fluorescence spectrum detection system based on laser-induced fluorescence(LIF)technology is built,and the fluorescence spectra of three different oils,i.e.,0^#diesel,95^#gasoline,and common kerosene,are obtained.Characteristic parameters are extracted from the spectral information.The standard deviation,center distance,and kurtosis coefficients of the fluorescence peak are taken as sensitive characteristic parameters for cluster analysis.Finally,the curve fitting method is used to quantitatively measure the mass concentration of samples.Experimental results show that the combination of LIF technology with the characteristic parameter extraction method and curve fitting method can be used for the qualitative and quantitative detection of different oil pollutants,which provides a new idea for their rapid identification and detection.
作者
陈至坤
郭蕊
程朋飞
Chen Zhikun;Guo Rui;Cheng Pengfei(College of Electrical Engineering,North China University of Science and Technology,Tangshan,Hebei 063210,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2020年第13期324-329,共6页
Laser & Optoelectronics Progress
基金
唐山市应用基础研究计划项目(18130204a)。
关键词
光谱学
激光诱导荧光
油类污染物
特征参量
聚类分析
spectroscopy
laser induced fluorescence
oil pollutants
characteristic parameter
cluster analysis
