Quantitative Analysis Model of Multi-Component Complex Oil Spill Source Based on Near Infrared Spectroscopy
TAN Ai-ling, BI Wei-hong*
College of Information Science and Engineering, Yanshan University, Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province, Qinhuangdao 066004, China
Abstract：Near infrared spectroscopy technology was used for quantitative analysis of the simulation of complex oil spill source. Three light petroleum products, i.e. gasoline, diesel fuel and kerosene oil, were selected and configured as simulated mixture of oil spill samples in accordance with different concentrations proportion, and their near infrared spectroscopy in the range of 8 000～12 000 cm-1 was collected by Fourier transform near infrared spectrometer. After processing the NIR spectra with different pretreatment methods, partial least squares method was used to establish quantitative analysis model for the mixture of oil spill samples. For gasoline, diesel fuel and kerosene oil, the second derivative method is the optimal pretreatment method, and for these three oil components in the ranges of 8 501.3~7 999.8 and 6 102.1~4 597.8 cm-1;6 549.5~4 597.8;7 999.8~7 498.4 and 102.1~4 597.8 cm-1, the correlation coefficients R2 of the prediction model are 0.998 2, 0.990 2 and 0.993 6 respectively, while the forecast RMSEP indicators are 0.474 7, 0.936 1 and 1.013 1 respectively; The experimental results show that using near infrared spectroscopy can quantitatively determine the content of each component in the simulated mixed oil spill samples, thus this method can provide effective means for the quantitative detection and analysis of complex marine oil spill source.
Key words：NIR spectroscopy;Complex oil spill source;Quantitative analysis model;Partial least squares
谈爱玲，毕卫红* . 基于近红外光谱法的多组分复杂溢油源定量建模分析 [J]. 光谱学与光谱分析, 2012, 32(12): 3203-3207.
TAN Ai-ling, BI Wei-hong*. Quantitative Analysis Model of Multi-Component Complex Oil Spill Source Based on Near Infrared Spectroscopy . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(12): 3203-3207.
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