Oil spill type recognition method based on fluorescence spectrum

A technology of oil spill recognition and recognition method, which is applied in the field of oil spill type recognition and pattern recognition based on fluorescence spectrum, can solve the problems of complex recognition process, limited identifiable types, weak self-adaptive ability, etc., and achieve simple recognition method and improved Efficiency and self-adaptability, the effect of improving recognition accuracy

Inactive Publication Date: 2010-12-22
OCEAN UNIV OF CHINA
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Problems solved by technology

[0005] Aiming at the problems of limited identifiable types, complicated identification process and weak self-adaptive ability in the oil spill type identification method in the prior art, the present invention provides an oil spill type iden

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  • Oil spill type recognition method based on fluorescence spectrum
  • Oil spill type recognition method based on fluorescence spectrum
  • Oil spill type recognition method based on fluorescence spectrum

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[0040] The technical solutions of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0041] First, briefly explain the starting point of the oil spill type identification method of the present invention: by analyzing the various oil fluorescence spectrum characteristics measured by the laser fluorescence radar system, it is found that light oils such as 90# gasoline, 93# gasoline and 97# gasoline and diesel oil The three types of oils, such as medium oil and lubricating oil, have obvious differences in the shape characteristics of fluorescence spectra, and compared with crude oil and heavy residual fuel oil, their spectral peaks are shifted forward, and the peak wavelength is relatively short, which is easy to distinguish. However, the spectral shape characteristics of crude oil and heavy residual fuel oil are slightly different, and cannot be simply distinguished linearly. Based on the abov...

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Abstract

The invention discloses an oil spill type recognition method based on a fluorescence spectrum, which comprises the processes of establishing an oil spill recognition model and recognizing oil spill types based on the oil spill recognition model, wherein the process of establishing the oil spill recognition model comprises the following steps: establishing a primary recognition model and establishing a secondary recognition model, wherein the secondary recognition model is the global optimum secondary recognition model which is selected by using a particle swarm optimization algorithm based onspectrums of known oil spill types; and the process of recognizing the oil spill types based on the oil spill recognition model comprises the following steps: using the primary recognition model to recognize the oil spill types, and judging whether to use the secondary recognition model for recognition according to the primary recognition result. By using a hierarchical recognition classificationmethod, the invention increases the quantity of recognizable oil spill types, and improves the recognition efficiency and the adaptive capability of the method.

Description

technical field [0001] The invention relates to a pattern recognition method, in particular to an oil spill type recognition method based on fluorescence spectrum, and belongs to the technical field of remote sensing monitoring. Background technique [0002] Among many remote sensing monitoring methods for oil pollution on the sea surface, airborne laser fluorescence radar is the most effective and potential one. High-speed, high-precision oil spill information helps relevant departments make decisions on oil spill emergency measures. [0003] At present, the United States, France, Canada, Germany, Japan and other countries have developed airborne marine laser fluorescence radar systems for monitoring oil pollution on the sea surface. In the more important data processing and analysis links in the system, these typical systems mainly use simple classification algorithms such as correlation or distance measurement, or more complex pattern recognition methods such as neural n...

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Application Information

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IPC IPC(8): G06K9/62G01N21/64G01N21/65
Inventor 赵朝方齐敏珺马佑军李晓龙
Owner OCEAN UNIV OF CHINA
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