Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy.

Journal: Marine pollution bulletin
Published Date:

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

  • Chunyan Wang
    School of Food Science, Henan Institute of Science and Technology, Xinxiang, 453003 China.
  • Xiaofeng Shi
    Department of Infectious Diseases, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Wendong Li
    Optics and Optoelectronics Laboratory, Ocean University of China, Qingdao 266100, China.
  • Lin Wang
    Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China.
  • Jinliang Zhang
    College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China.
  • Chun Yang
    State Key Laboratory of Biogeology and Environmental Geology, School of Earth Sciences, China University of Geosciences, Wuhan, 430074, China.
  • Zhendi Wang
    Emergencies Science and Technology Section(ESTS), Science and Technology Branch, Environment Canada, 335 River Rd., Ottawa, Ontario K1A 0H3, Canada.