Iron Ore Tailing Composition Estimation Using Fused Visible–Near Infrared and Thermal Infrared Spectra by Outer Product Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Tailing Sample Collection
2.2. Spectral Measurement
2.3. Data Preprocessing Method
2.4. Spectral Fusion Method
2.5. Spectroscopic Modeling Method
3. Results and Discussion
3.1. VIS–NIR Spectral and Absorption Characteristics
3.2. TIR Spectral and Absorption Characteristics
3.3. Spectral Data Fusion and Coevolution
3.4. Correlation of Spectral Data with TFe and SiO2 Content
3.5. Prediction Accuracy of TFe and SiO2
4. Conclusions
- This study demonstrated that with the VIS–NIR spectra, the sensitive absorption bands of SiO2 occurred in the ranges of 1365–1391 nm and 1410–1623 nm, and those of TFe occurred in the range of 1163–2499 nm. In the TIR domain, the sensitive absorption bands of both SiO2 and TFe were in the ranges of 8–9.4 μm and 10.7–12 μm.
- Compared with individual VIS–NIR or TIR spectra, the OPA-fused absorbance data had a stronger correlation with TFe and SiO2 content. The largest correlation coefficient between TFe and the fusion domain (1181–1409 nm and 2298–2375 nm for VIS–NIR, 8.17–8.27 μm, and 8.37–8.52 μm for TIR) was 0.87. By contrast, the largest correlation coefficient between SiO2 and the fusion domain (1257–1714 nm for VIS–NIR and 8.13–0.54 μm for TIR) was 0.84.
- The combination of RF modeling and OPA-fused spectral data achieved the optimal prediction accuracy of TFe and SiO2 compared with the accuracy obtained through individual spectra. The R2 value increased from 0.70 to 0.91, RMSE decreased from 1.60% to 0.96%, and RPIQ increased from 1.25 to 2.31 for TFe prediction. The R2 value increased from 0.67 to 0.95, RMSE decreased from 2.49% to 0.97%, and RPIQ increased from 2.52 to 6.49 for SiO2 prediction. The RF model performed better than the PLSR and PSO–ELM models, with greater R2 and RPIQ and lower RMSE values.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Input Spectral Region | Tailings Content | Model | R2 | RMSE (%) | RPIQ | |
---|---|---|---|---|---|---|
VIS–NIR | 1365–1391 nm 1410–1623 nm | SiO2 | PLSR | 0.75 | 2.53 | 2.22 |
RF | 0.86 | 1.51 | 4.15 | |||
PSO–ELM | 0.87 | 1.49 | 3.91 | |||
1163–2499 nm | TFe | PLSR | 0.77 | 1.36 | 1.48 | |
RF | 0.86 | 1.08 | 2.05 | |||
PSO–ELM | 0.85 | 1.03 | 1.88 | |||
TIR | 8–9.4 μm 10.7–12 μm | SiO2 | PLSR | 0.55 | 3.04 | 1.84 |
RF | 0.67 | 2.49 | 2.52 | |||
PSO–ELM | 0.60 | 2.88 | 1.99 | |||
TFe | PLSR | 0.70 | 1.60 | 1.25 | ||
RF | 0.54 | 1.88 | 1.18 | |||
PSO–ELM | 0.62 | 1.83 | 1.14 | |||
Fused | Bands of |r|≥ 0.80 | SiO2 | PLSR | 0.74 | 2.16 | 2.59 |
RF | 0.95 | 0.97 | 6.49 | |||
PSO–ELM | 0.94 | 1.32 | 2.33 | |||
TFe | PLSR | 0.84 | 1.22 | 1.64 | ||
RF | 0.91 | 0.96 | 2.31 | |||
PSO–ELM | 0.89 | 1.14 | 1.75 | |||
Augmentation | 1365–1391 nm 1410–1623 nm 8–9.4 μm 10.7–12 μm | SiO2 | PLSR | 0.74 | 2.18 | 1.89 |
RF | 0.90 | 1.28 | 4.90 | |||
PSO–ELM | 0.88 | 1.72 | 3.40 | |||
1163–2499 nm 8–9.4 μm 10.7–12 μm | TFe | PLSR | 0.82 | 1.17 | 2.11 | |
RF | 0.87 | 1.10 | 2.02 | |||
PSO–ELM | 0.86 | 1.07 | 1.52 |
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Bao, N.; Lei, H.; Cao, Y.; Liu, S.; Gu, X.; Zhou, B.; Fu, Y. Iron Ore Tailing Composition Estimation Using Fused Visible–Near Infrared and Thermal Infrared Spectra by Outer Product Analysis. Minerals 2022, 12, 382. https://doi.org/10.3390/min12030382
Bao N, Lei H, Cao Y, Liu S, Gu X, Zhou B, Fu Y. Iron Ore Tailing Composition Estimation Using Fused Visible–Near Infrared and Thermal Infrared Spectra by Outer Product Analysis. Minerals. 2022; 12(3):382. https://doi.org/10.3390/min12030382
Chicago/Turabian StyleBao, Nisha, Haimei Lei, Yue Cao, Shanjun Liu, Xiaowei Gu, Bin Zhou, and Yanhua Fu. 2022. "Iron Ore Tailing Composition Estimation Using Fused Visible–Near Infrared and Thermal Infrared Spectra by Outer Product Analysis" Minerals 12, no. 3: 382. https://doi.org/10.3390/min12030382
APA StyleBao, N., Lei, H., Cao, Y., Liu, S., Gu, X., Zhou, B., & Fu, Y. (2022). Iron Ore Tailing Composition Estimation Using Fused Visible–Near Infrared and Thermal Infrared Spectra by Outer Product Analysis. Minerals, 12(3), 382. https://doi.org/10.3390/min12030382