Statistics – Applications
Scientific paper
Feb 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005spie.5634..153s&link_type=abstract
Advanced Sensor Systems and Applications II. Edited by Rao, Yun-Jiang; Kwon, Osuk Y.; Peng, Gang-Ding. Proceedings of the SPIE,
Statistics
Applications
Scientific paper
To realize the on-line fluorescence monitoring of mineral oil pollution in water, three-dimensional spectral characteristic of oil-water intermixtures must be studied and the characteristic must be extracted. Using excitation wavelength, fluorescence wavelength and fluorescence intensity as three-dimensional system of coordinate, through sampling and surface fitting, three-dimensional fluorogram is gotten, which can provide gist for oil discrimination when presented in contour chart (finger-print map of oils). But there is little difference between characteristics of three-dimensional fluorogram because of the similarity of constituent and structure of similar oils. Therefore this paper introduces quantitative analysis method-characteristic parameter method which starts with analyzing statistical characteristic of three-dimensional fluorogram. Using RFPC fluorescence spectrometer (Shimadzu, Japan), three-dimensional fluorescence spectra of diesel oil, machine oil, gasoline oil, crude oil are measured and parameterized. The result shows that as a quantitative classified discrimination method of three-dimensional fluorescence spectra, the parameter of characteristic parameter method possesses definiteness for three-dimensional fluorescence spectra, and it is applicable, available when used in oil discrimination.
Liu Xian-yong
Shang L.-L.
Xu Jingjun
Xu Xiaoxuan
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