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Research on marine oil spill identification based on laser-induced fluorescence LiDAR

  • Qingsheng Xue,
  • Junhong Song,
  • Fengqin Lu,
  • Jun Ma,
  • Xinyu Gao,
  • Jinfeng Xu

摘要

The rise in oil extraction and transportation in marine environments has led to frequent oil spill incidents, posing a severe threat to marine ecosystems and becoming an urgent environmental issue. This paper presents a laser-induced fluorescence light detection and ranging (LiDAR) system specifically designed for monitoring marine oil spills. The system comprises a laser emission module, a receiving module, a data processing module, and a wireless transmission module. Through outdoor experiments, the system has demonstrated its effectiveness and reliability in detecting and identifying various oil types, including crude oil, diesel, heavy oil, gasoline, and lubricating oil. Additionally, a BP neural network model was employed to process the fluorescence spectral data collected by the LiDAR system. This model successfully predicted oil types with an accuracy of 96.58%. This research presents a new technological solution for marine oil spill monitoring, offering significant potential for practical applications and further research.