title: Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy.
abstract: Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 crude oil samples from the Bohai Sea platforms of China was carried out under controlled laboratory conditions and showed that weathering had no significant effect on the CSMF spectra. While different feature extraction methods, such as PCA, PLS and Gabor wavelet analysis, were applied to extract discriminative patterns from CSMF spectra, classifications were made via SVM to compare their respective performance of oil species recognition. Ideal correct rates of oil species recognition of 100% for the different types of oil spill samples and 92% for the closely-related source oil samples were achieved by combining Gabor wavelet with SVM, which indicated its advantages to be developed to a rapid, cost-effective, and accurate forensic oil spill identification technique.
authors.affiliation: Department of Physics and Electronic Science, Weifang University, Weifang 261061, China; College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China; Optics and Optoelectronics Laboratory, Ocean University of China, Qingdao 266100, China; Emergencies Science and Technology Section(ESTS), Science and Technology Branch, Environment Canada, 335 River Rd., Ottawa, Ontario K1A 0H3, Canada.
authors.forename: Chunyan
authors.initials: C
authors.lastname: Wang
authors.affiliation: Optics and Optoelectronics Laboratory, Ocean University of China, Qingdao 266100, China.
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Shi
authors.affiliation: Optics and Optoelectronics Laboratory, Ocean University of China, Qingdao 266100, China.
authors.forename: Wendong
authors.initials: W
authors.lastname: Li
authors.affiliation: Department of Physics and Electronic Science, Weifang University, Weifang 261061, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Wang
authors.affiliation: College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China.
authors.forename: Jinliang
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Emergencies Science and Technology Section(ESTS), Science and Technology Branch, Environment Canada, 335 River Rd., Ottawa, Ontario K1A 0H3, Canada.
authors.forename: Chun
authors.initials: C
authors.lastname: Yang
authors.affiliation: Emergencies Science and Technology Section(ESTS), Science and Technology Branch, Environment Canada, 335 River Rd., Ottawa, Ontario K1A 0H3, Canada.
authors.forename: Zhendi
authors.initials: Z
authors.lastname: Wang
mesh_terms: D002681:China; D004784:Environmental Monitoring / Q000379:methods*; D005453:Fluorescence; D010578:Petroleum / Q000032:analysis*; D059392:Petroleum Pollution / Q000032:analysis*; D025341:Principal Component Analysis; D013050:Spectrometry, Fluorescence; D060388:Support Vector Machine; D014874:Water Pollutants, Chemical / Q000032:analysis*; D058067:Wavelet Analysis
chemical_list: D010578:Petroleum; D014874:Water Pollutants, Chemical
keywords: Concentration-synchronous-matrix-fluorescence (CSMF); Gabor wavelet analysis; Oil spill; Partial least square analysis (PLS); Principle component analysis (PCA); Supported vector machine (SVM)