Suling Qiu, An Li, Xianshuang Wang, Denan Kong, Xiao Ma, Yage He, Yunsong Yin, Yufei Liu, Lijie Shi, Ruibin Liu. High-accuracy Quantitatively Analysis of Iron Content in Mineral Based on Laser-Induced Breakdown Spectroscopy[J]. Chinese Journal of Lasers, 2021, 48(16): 1611002
- Chinese Journal of Lasers
- Vol. 48, Issue 16, 1611002 (2021)
Fig. 1. Experimental apparatus and optical path
Fig. 2. Performance results of anomalous spectrum. (a) Comparison of abnormal and normal spectra; (b) spectral line fluctuation before and after removal of abnormal spectrum
Fig. 3. Partial original spectrograms of three types of ores. (a) GBW07820; (b) ZBK332; (c) YSBC28766-2008
Fig. 4. Explanation rates and scores of different principal components. (a) Interpretation rate of each principal component and cumulative interpretation rate of each principal component; (b) 3D scores of first three principal components
Fig. 5. Calibration curves of full spectrum PLS. (a) 35 kinds of ore species; (b) 14 kinds of iron ore; (c) 12 kinds of manganese ores; (d) 9 kinds of chromium ores
Fig. 6. Relationship between RMSEP and correlation coefficient C
Fig. 7. Relationship between RMSEP and modeling set determination coefficient with number of principal components
Fig. 8. Calibration curves for R-PLS. (a) 14 kinds of iron ore; (b) 12 kinds of manganese ore; (c) 9 kinds of chromium ore; (d) all ores
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Table 1. Sample type and Fe content of iron ore, manganese ore, and chromium ore
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Table 2. Classification results of three different kinds of ore by support vector machine model
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Table 3. Classification and comparison of quantitative analysis results before and after R-PLS
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