Paper
9 September 2002 Fluorescence optical fiber measurement system for identification of oil type based on 3D fluorescence spectrum parameterization
Liping Shang, Ying Wang, Jinshan Shi
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Abstract
In this paper, a portable fluorescence optical-fiber measurement system for identification of oil species is presented, which is based on fluorescence spectrum analysis, and combines the optical-fiber sensing technique and computer data processing technique. Fluorescence spectroscopy is enjoying increasing popularity as a technique for qualitative and quantitative analysis. Because of its great sensitivity, it is becoming an important tool for the identification of the type pf oil especially at low concentration levels. Conventional fluorescence methods suffer from low selectivity and are generally ineffective in spectral structural elucidation of carious oils because the different oil has fluorescence spectrum overlapping to great extent. The three-dimensional fluorescence spectroscopy overcomes the above-mentioned shortcomings. In this paper, the principle of 3-D fluorescence spectrum parameterization is introduced as a new spectral analysis method. The main feature parameters are mean, standard deviation, origin moment, marginal distribution, center moment, correlation coefficient and compression ellipse. We obtain the 3-D fluorescence spectrum of four kinds oils (crude oil, diesel fuel, kerosene, machine oil) by using fluorescence spectrophotometer in the lab and extract the feature parameters, which are weighting processed according to their sensitivity to the oil species for identification. The result suggests the degree of accuracy is as high as 95%.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Liping Shang, Ying Wang, and Jinshan Shi "Fluorescence optical fiber measurement system for identification of oil type based on 3D fluorescence spectrum parameterization", Proc. SPIE 4920, Advanced Sensor Systems and Applications, (9 September 2002); https://doi.org/10.1117/12.481982
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KEYWORDS
Luminescence

Neural networks

Optical fibers

Optical testing

System identification

3D metrology

3D modeling

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