Acta Photonica Sinica, Volume. 46, Issue 9, 930002(2017)
Concentration Detection of Polycyclic Aromatic Hydrocarbon Combining Three-dimensional Fluorescence Spectroscopy with HGA-RBF Neural Network
Three-dimensional excitation-emission matrix fluorescence spectroscopy of Benzo [k] Fluoranthene (BkF), Benzo [b] Fluoranthene (BbF), and a mixture of these two substances were analyzed with FS920 fluorescence spectrometer. The results show that the fluorescence peaks of BkF can be observed at 306 nm/405 nm and 306 nm/430 nm, and the fluorescence peaks of BbF locate at 306 nm/410 nm and 306 nm/435 nm. In the mixture of BkF and BbF, concentration ratio and fluorescence interferences make excitation-emission matrix spectra of mixture change largely. Hence, the relationship between fluorescence intensity and concentration is complicated. In order to determine the concentration of BkF and BbF in mixture, radial basis function neural network optimized by hierarchical genetic algorithm was applied and the average recovery of BkF and BbF are 98.45% and 97.71%, respectively. The results showed that the possibility of the identification and concentration prediction of different components in mixed sample of polycyclic aromatic hydrocarbons.
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WANG Shu-tao, ZHENG Ya-nan, WANG Zhi-fang, MA Xiao-qing, WANG Chang-bing, CHENG Qi. Concentration Detection of Polycyclic Aromatic Hydrocarbon Combining Three-dimensional Fluorescence Spectroscopy with HGA-RBF Neural Network[J]. Acta Photonica Sinica, 2017, 46(9): 930002
Received: Mar. 8, 2017
Accepted: --
Published Online: Oct. 16, 2017
The Author Email: Shu-tao WANG (wangshutao@ysu.edu.cn)