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基于LIF的海面溢油状态识别研究
引用本文:袁 丽,谢贝贝,崔永强,张晓丹,焦慧慧. 基于LIF的海面溢油状态识别研究[J]. 光谱学与光谱分析, 2022, 42(7): 2018-2024. DOI: 10.3964/j.issn.1000-0593(2022)07-2018-07
作者姓名:袁 丽  谢贝贝  崔永强  张晓丹  焦慧慧
作者单位:成都信息工程大学计算机学院,四川 成都 610225;燕山大学信息科学与工程学院,河北 秦皇岛 066004
基金项目:国家科技重大专项(2017ZX05019001-011)资助
摘    要:随着海洋运输业和海洋石油开采业的快速发展,溢油污染日益严重,给海洋环境和海洋生态平衡带来极大威胁。因此海洋溢油污染的治理、改善,成为海洋环境保护工程中刻不容缓的重要工作。而对不同状态溢油的识别则是解决溢油污染问题的基础与关键。海面上的溢油,主要包括未乳化与乳化两个不同阶段。前者以不同厚度的油膜形式存在,后者以不同油水比的溢油乳化物形式存在。不同状态的海面溢油具有不同的元素组成:油膜为纯油分子,乳化溢油为油水混合结构,构建出差异化的荧光基团。在激光作用下具备各自特征的荧光光谱信息,不同状态显示出较为明显的荧光光谱差异。光谱曲线的形状特征是荧光物质物理化学性质的一种外在体现,所以从光谱的特征形状来分析、比较一定的光谱参量可以达到物质分类和物种识别的目的和效果。为了实现海面溢油不同状态的快速分类识别,通过搭建的LIF探测系统,采集了常用成品油不同状态的荧光光谱,光谱曲线对比发现:乳化阶段的光谱会表现出荧光峰个数增多、荧光强度改变、荧光峰位偏移等一系列特征。在此基础上,根据表观统计学原理,提取光谱的均值、标准差、峰度系数、谱线宽度、曲线斜率等特征参量,并将这些特征值进行聚类分析。结果显示:基于...

关 键 词:激光诱导荧光  荧光光谱  溢油乳化物  特征参量  聚类分析
收稿时间:2021-06-29

Research on Oil Spill Status Recognition Based on LIF
YUAN Li,XIE Bei-bei,CUI Yong-qiang,ZHANG Xiao-dan,JIAO Hui-hui. Research on Oil Spill Status Recognition Based on LIF[J]. Spectroscopy and Spectral Analysis, 2022, 42(7): 2018-2024. DOI: 10.3964/j.issn.1000-0593(2022)07-2018-07
Authors:YUAN Li  XIE Bei-bei  CUI Yong-qiang  ZHANG Xiao-dan  JIAO Hui-hui
Affiliation:1. School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China2. College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China
Abstract:With the rapid development of the marine transportation industry and the offshore oil exploitation industry, oil spill pollution is becoming increasingly serious, posing a great threat to the marine environment and ecological balance. Therefore, the treatment and improvement of oil spill pollution have become an urgent and important work in marine environmental protection engineering. The identification of oil spills in different states is the basis and key to solving the problem of oil spill pollution. The oil spill on the sea mainly includes two different stages: non-emulsification and emulsification. The former is in the form of oil film with different thicknesses, while the latter is in oil spill emulsion with different oil-water ratios. The oil spill in different states has different element compositions: the oil film is a pure oil molecule, the emulsified oil spill is an oil-water mixed structure, and the fluorescent group is formed. Under the action of the laser, it has its own characteristic fluorescence spectrum information, and different states show obvious fluorescence spectrum differences. The shape feature of the spectral curve is an external manifestation of fluorescent substances’ physical and chemical properties, so analyzing and comparing certain spectral parameters from the shape feature of the spectrum can achieve the purpose and effect of substance classification and species identification. In order to realize the rapid classification and identification of different states of oil spills on the sea, the LIF detection system was built to collect the fluorescence spectra of common oil products in different states. The comparison of the spectral curves shows that the spectrum in the emulsification stage will show a series of characteristics, such as the increase in the number of fluorescence peaks, the change of fluorescence intensity, the shift of fluorescence peak position and so on. According to the principle of apparent statistics, the mean value, standard deviation, kurtosis coefficient, spectral linewidth, curve slope and other characteristic parameters of the spectrum are extracted, and these characteristic values are used for cluster analysis. The results show that the cluster analysis results of oil spills based on laser-induced fluorescence spectrum are consistent with the actual oil spill status. Based on the premise of known oil species, the classification method can better identify different oil spill states on the sea. Therefore, this method can provide a new idea for identifying oil spills on the sea and lay a foundation for the improvement of LIF technology detection quality and application level.
Keywords:Laser induced fluorescence  Fluorescence spectrum  Oil spill emulsions  Characteristic parameter  Cluster analysis  
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