基于三维荧光光谱和小波分析的油品种类识别技术研究
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摘要
随着我国经济的不断发展和对能源需求的增加，海洋石油工业和海上石油运输得到蓬勃发展，导致我国的海洋石油污染情况日趋严重。近年，我国海上不明溢油源污染事故频频发生。2006年初以来，渤海海域每年春冬季节，先后多次发现不明来源的污染物，2008年6月秦皇岛海岸线、2010年4月青岛近海海域分别发现不明来源溢油。我国政府防止石油污染海洋，保护海洋生态环境和资源的任务非常艰巨。溢油鉴别是确定海上溢油事故污染源的重要的科技手段之一，在污染事故调查处理中发挥着非常重要的作用。在溢油鉴别工作中，当发现海上不明溢油源时，首先要进行的便是油种鉴定工作。海上常见的油品种类有原油、柴油、船舶燃料油和船舶机舱污油，海上不同油种的来源不同，溢油来源的查找方向也不同，因此，快速、准确的油种鉴定工作能够为事故调查人员快速指明调查方向，缩小调查范围，缩短调查周期，提高事故调查效率，是海上不明溢油源调查工作成功开展的重要前提和基础。
本研究针对我国海上溢油事故中常见的4大类6种油品的三维荧光光谱开展了系统的油种识别技术研究，通过小波分析、光谱相似度比较、Fisher判别分析、Bayes判别分析确定了适合于油品三维荧光光谱数据的小波特征谱；开展了油品模拟风化实验，考察了油品三维荧光光谱的风化变化规律，并评价了风化过程对油品三维荧光光谱的改变是否会对油种识别结果产生影响；利用系统聚类法，对不同油种油品的小波特征谱进行归类，并建立油种的标准特征谱；建立了基于油品三维荧光光谱标准特征谱的油种识别方法，并在海上不明溢油源事故中得到应用。取得的主要成果如下：
（1）通过bior族小波基、db族小波基、symmlet族小波基、coiflet族小波基共4种小波函数对油品三维荧光光谱特征谱的重构效果比较，并借助Fisher判别法和Bayes判别法对特征谱分类识别能力的研究，发现油样Em矩阵db7小波ca3特征谱和Ex矩阵db7小波ca3特征谱的油种识别能力比较理想，可作油种识别中的特征谱。特征谱对轻油的识别正确率为86.54%、船舶污油的识别正确率为61.70%，原油的识别正确率为66.67%，燃料油大类识别正确率为的94.44%。
（2）通过开展风化模拟实验，发现风化过程不会改变油样三维荧光光谱的分布特征，但能够改变荧光特征峰的相对强度，变化趋势与特征峰的位置有关。风化过程对油品三维荧光光谱特征谱的变化，要小于不同油种之间三维荧光光谱特征谱之间的差异，短期的风化过程不会对油种识别结果产生影响。
（3）建立了柴油、120CST燃料油、180CST燃料油、380CST燃料油、船舶污油、原油共4大类6种油种的三维荧光光谱标准特征谱，其中Em矩阵ca3特征谱获得21条标准特征谱、Ex矩阵ca3特征谱获得19条标准特征谱。
（4）初步建立了基于油品三维荧光光谱标准特征谱的油种识别方法，并在海上不明溢油源事故中成功应用。结果表明，油种标准特征谱对燃料油的识别正确率为100%。对于识别正确的油样，其三维荧光光谱特征谱与标准特征谱的相似度指数均达到0.9700以上。可以考虑将光谱相似度指数0.9700作为油种识别正确与否的判别标准，相似度指数≥0.9700时识别结果有效，从而实现对识别结果正确性的初步评价。
With the rapid economic development and the increased energy demand of China,marine petroleum industry and marine petroleum transportation develops rapidly,which lead to the serious oil pollution situation of Chinese marine environment.Unknown source oil spill accidents happened frequently in China in these years:spilled oil was found in Bohai area every winter-spring season since2006; unknownsource oil pollution happened around Qinhuangdao coast in June2008and Qingdaocoast in April2010. It is a hard work for China government to prevent oil pollutionand to protect marine ecology environment and resources. Oil fingerprintingidentification is one of the technology methods to search the source of spilled oil,which plays an important role in pollution accident investigates. During oilfingerprinting identification, the first step is usually to identify spilled oil types, whichcould provide clear direction for investigation personnel. A correct oil type could helpto reduce investigation range and time and enhance investigation efficiency, which isthe premise and foundation of the success of accident investigation.
This paper aims to study the3D fluorescence spectroscopy characters of differentoil types. Six kinds of oil that are diesel oil,120CST fuel oil,180CST fuel oil,380CST fuel oil, vessel waste oil and crude oil, which belongs to four type of oil, areselected. The fingerprint characters of the3D fluorescence spectroscopy are extractedand analyzed by the wavelet analysis, Fisher discriminant analysis and Bayesdiscriminant analysis to select the reference spectra extracted by wavelets. Aweathering experiment is presented to research the fingerprinting characters changedby weathering and to evaluate whether the oil types discriminating result could bechanged by the influence of weathering. The standard reference spectrum are obtainedby clustering analysis and applied in oil pollution accident investigation. The mainconclusions of this paper are as follows:
(1) The correlation of the original spectra and reconstruct spectra obtained by Bior wavelets, Coiflet wavelets, Daubechies wavelets and Symmlet wavelets and the oiltype discriminating ability of reference spectrum are researched, which shows that thedb7wavelets third scale-series discriminating characteristic spectra both for thematrix transported from emission direction and matrix transported from excitationdirection has a better distinguish ability. The discriminating correct rates of thereference spectrum are66.67%(crude oil),86.54%(diesel oil),94.44%(fuel oil) and61.70%(vessel waste oil).
(2) The weathering experiment research shows that weathering couldn’t changeoil fluorescence spectroscopy characters but could change relative intensity offluorescence signal peak, whose change direction is depended on the peak position.Change of fluorescence spectroscopy characters during the weathering experiment islittle than the fluorescence spectroscopy difference between different oil types. Thedistinguish ability of reference spectrum couldn’t be influenced by Short-termweathering.
(3) Standard reference fluorescence spectra of diesel oil,120CST fuel oil,180CSTfuel oil,380CST fuel oil, vessel waste oil and crude oil are constructed. There are21characteristic spectra of the db7wavelets third scale-series for the matrix transportedfrom emission direction and19characteristic spectra of the db7wavelets thirdscale-series for the matrix transported from excitation direction.
(4) Oil type discriminating method based on the fluorescence spectroscopy andwavelets analysis is set up and applied in four oil pollution accidents investigation.The discriminating correct rate of the reference spectrum to fuel oil is100%. In thediscriminating results, the similarity indexes between the standard reference spectraand the reference spectra of testing oil samples that has a right discriminating resultare all above0.9700. The similarity index0.9700could be used as a standard toevaluate whether the discriminating result is correct. Similarity index of a correctresult should be not less than0.9700.
本研究针对我国海上溢油事故中常见的4大类6种油品的三维荧光光谱开展了系统的油种识别技术研究，通过小波分析、光谱相似度比较、Fisher判别分析、Bayes判别分析确定了适合于油品三维荧光光谱数据的小波特征谱；开展了油品模拟风化实验，考察了油品三维荧光光谱的风化变化规律，并评价了风化过程对油品三维荧光光谱的改变是否会对油种识别结果产生影响；利用系统聚类法，对不同油种油品的小波特征谱进行归类，并建立油种的标准特征谱；建立了基于油品三维荧光光谱标准特征谱的油种识别方法，并在海上不明溢油源事故中得到应用。取得的主要成果如下：
（1）通过bior族小波基、db族小波基、symmlet族小波基、coiflet族小波基共4种小波函数对油品三维荧光光谱特征谱的重构效果比较，并借助Fisher判别法和Bayes判别法对特征谱分类识别能力的研究，发现油样Em矩阵db7小波ca3特征谱和Ex矩阵db7小波ca3特征谱的油种识别能力比较理想，可作油种识别中的特征谱。特征谱对轻油的识别正确率为86.54%、船舶污油的识别正确率为61.70%，原油的识别正确率为66.67%，燃料油大类识别正确率为的94.44%。
（2）通过开展风化模拟实验，发现风化过程不会改变油样三维荧光光谱的分布特征，但能够改变荧光特征峰的相对强度，变化趋势与特征峰的位置有关。风化过程对油品三维荧光光谱特征谱的变化，要小于不同油种之间三维荧光光谱特征谱之间的差异，短期的风化过程不会对油种识别结果产生影响。
（3）建立了柴油、120CST燃料油、180CST燃料油、380CST燃料油、船舶污油、原油共4大类6种油种的三维荧光光谱标准特征谱，其中Em矩阵ca3特征谱获得21条标准特征谱、Ex矩阵ca3特征谱获得19条标准特征谱。
（4）初步建立了基于油品三维荧光光谱标准特征谱的油种识别方法，并在海上不明溢油源事故中成功应用。结果表明，油种标准特征谱对燃料油的识别正确率为100%。对于识别正确的油样，其三维荧光光谱特征谱与标准特征谱的相似度指数均达到0.9700以上。可以考虑将光谱相似度指数0.9700作为油种识别正确与否的判别标准，相似度指数≥0.9700时识别结果有效，从而实现对识别结果正确性的初步评价。
With the rapid economic development and the increased energy demand of China,marine petroleum industry and marine petroleum transportation develops rapidly,which lead to the serious oil pollution situation of Chinese marine environment.Unknown source oil spill accidents happened frequently in China in these years:spilled oil was found in Bohai area every winter-spring season since2006; unknownsource oil pollution happened around Qinhuangdao coast in June2008and Qingdaocoast in April2010. It is a hard work for China government to prevent oil pollutionand to protect marine ecology environment and resources. Oil fingerprintingidentification is one of the technology methods to search the source of spilled oil,which plays an important role in pollution accident investigates. During oilfingerprinting identification, the first step is usually to identify spilled oil types, whichcould provide clear direction for investigation personnel. A correct oil type could helpto reduce investigation range and time and enhance investigation efficiency, which isthe premise and foundation of the success of accident investigation.
This paper aims to study the3D fluorescence spectroscopy characters of differentoil types. Six kinds of oil that are diesel oil,120CST fuel oil,180CST fuel oil,380CST fuel oil, vessel waste oil and crude oil, which belongs to four type of oil, areselected. The fingerprint characters of the3D fluorescence spectroscopy are extractedand analyzed by the wavelet analysis, Fisher discriminant analysis and Bayesdiscriminant analysis to select the reference spectra extracted by wavelets. Aweathering experiment is presented to research the fingerprinting characters changedby weathering and to evaluate whether the oil types discriminating result could bechanged by the influence of weathering. The standard reference spectrum are obtainedby clustering analysis and applied in oil pollution accident investigation. The mainconclusions of this paper are as follows:
(1) The correlation of the original spectra and reconstruct spectra obtained by Bior wavelets, Coiflet wavelets, Daubechies wavelets and Symmlet wavelets and the oiltype discriminating ability of reference spectrum are researched, which shows that thedb7wavelets third scale-series discriminating characteristic spectra both for thematrix transported from emission direction and matrix transported from excitationdirection has a better distinguish ability. The discriminating correct rates of thereference spectrum are66.67%(crude oil),86.54%(diesel oil),94.44%(fuel oil) and61.70%(vessel waste oil).
(2) The weathering experiment research shows that weathering couldn’t changeoil fluorescence spectroscopy characters but could change relative intensity offluorescence signal peak, whose change direction is depended on the peak position.Change of fluorescence spectroscopy characters during the weathering experiment islittle than the fluorescence spectroscopy difference between different oil types. Thedistinguish ability of reference spectrum couldn’t be influenced by Short-termweathering.
(3) Standard reference fluorescence spectra of diesel oil,120CST fuel oil,180CSTfuel oil,380CST fuel oil, vessel waste oil and crude oil are constructed. There are21characteristic spectra of the db7wavelets third scale-series for the matrix transportedfrom emission direction and19characteristic spectra of the db7wavelets thirdscale-series for the matrix transported from excitation direction.
(4) Oil type discriminating method based on the fluorescence spectroscopy andwavelets analysis is set up and applied in four oil pollution accidents investigation.The discriminating correct rate of the reference spectrum to fuel oil is100%. In thediscriminating results, the similarity indexes between the standard reference spectraand the reference spectra of testing oil samples that has a right discriminating resultare all above0.9700. The similarity index0.9700could be used as a standard toevaluate whether the discriminating result is correct. Similarity index of a correctresult should be not less than0.9700.
引文
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