Zhongdong Wang, Yungang Zhang, Liangjing Zhang, liuqiang Wu. Research on Three-Dimensional Fluorescence Spectrum Identification Technology of Petroleum Pollutants Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2023, 60(15): 1530001
- Laser & Optoelectronics Progress
- Vol. 60, Issue 15, 1530001 (2023)
Fig. 1. Structure principle of CNN
Fig. 2. Blank water. (a) Three-dimensional fluorescence spectra; (b) contour maps
Fig. 3. Original C10-92# gasoline. (a) Three-dimensional fluorescence spectra; (b) contour maps
Fig. 4. C10-92# gasoline after elimination of Rayleigh scattering. (a) Three-dimensional fluorescence spectra; (b) contour maps
Fig. 5. C10-machine oil and C10-10# diesel oil after elimination of Rayleigh scattering. (a) Three-dimensional fluorescence spectra of C10-machine oil; (b) contour maps of C10-machine oil; (c) three-dimensional fluorescence spectra C10-10# diesel oil; (d) contour maps of C10-10# diesel oil
Fig. 6. Machine oil+gasoline. (a) Three-dimensional fluorescence spectra; (b) contour maps
Fig. 7. Machine oil+diesel oil. (a) Three-dimensional fluorescence spectra; (b) contour maps
Fig. 8. Gasoline+diesel oil. (a) Three-dimensional fluorescence spectra; (b) contour maps
Fig. 9. Machine oil+gasoline+diesel oil. (a) Three-dimensional fluorescence spectra; (b) contour maps
Fig. 10. Flow chart of deep learning model
Fig. 11. Deep learning model training process curves. (a) Classification accuracy; (b)loss function
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Table 1. Mass concentration configuration of experimental samples
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Table 2. Oil sample mixing method
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Table 3. Test result of petroleum spectra
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Table 4. Results of classification test of petroleum spectra
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