|
|
|
|
|
|
A FeO/TFe Determination Method of BIF Based on the Visible and Near-Infrared Spectrum |
MAO Ya-chun, WANG Dong, WANG Yue, LIU Shan-jun* |
School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China |
|
|
Abstract The FeO/TFe of iron ore is an important index to evaluate the industrial value of iron ore and classify the industrial type of ore. The conventional FeO/TFe measurements cost a lot of labor with low efficiency and long period, which are not benefit for the economical, reasonable and effective iron ore exploitation. Firstly, the visible and near-infrared spectrums of the BIF samples from Anqian mining area of Liaoning province were measured and the spectral features were analyzed. Then, three indexes of ration index (RI), difference index (DI) and normalized difference index (NDI) were put forward for analyzing the correlation relations between the indexes and FeO/TFe, and exploring the sensitive waveband. The experimental results showed that the sensitive waveband results of FeO/TFe from these three indexes are all located at 935 and 1 050 nm. All of these three correlation coefficients are larger than 0.9 at these two wavelength and the maximum value is 0.971 for the RI. Therefore, the inversion model for FeO/TFe according to RI results can be established and verified based on the laboratory report. The prediction error of FeO/TFe is 0.038 and the coefficient of determination (R2) is 0.964 5. The experimental results can provide a new economical and effective approach for determining the FeO/TFe of BIF and mine exploring via remote sensing.
|
Received: 2017-04-01
Accepted: 2017-09-05
|
|
Corresponding Authors:
LIU Shan-jun
E-mail: liusjdr@126.com
|
|
[1] HOU Zong-lin(候宗林). Contributions to Geology and Mineral Resources Research(地质找矿论丛), 2005, 20(4): 242.
[2] Mamdouh O, Timo F, Ahmed M, et al. Applied Surface Science, 2015, 345: 127.
[3] Mao Y C, Ma B D, Liu S J, et al. Canadian Journal of Remote Sensing, 2014, 40: 327.
[4] Hecker C, Meijde M, Meer F, et al. Earth-Science Reviews, 2010, 103: 60.
[5] Walid S, Mourtada E A, Reinhard G. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 136: 1816.
[6] Magendran T, Sanjeevi S. Journal of the Geological Society of India, 2013, 82(3): 227.
[7] Smith M R, Bandfield J L, Cloutis E A, et al. Icarus, 2013, 223(2): 633.
[8] SONG Liang, LIU Shan-jun, YU Mo-li, et al(宋 亮, 刘善军, 虞茉莉, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2017, 37(2): 416.
[9] WANG Run-sheng(王润生). Journal of Geo-Information Science(地球信息科学学报), 2009, 11(3): 261.
[10] Ganesh B P, Aravindan S, Raja S. Arabian Journal of Geosciences, 2013, 6(9): 3249.
[11] Salem S M, Gammal E. The Egyptian Journal of Remote Sensing and Space Sciences, 2015, 18(2): 195.
[12] Bishop J L, Murad E. American Mineralogist, 2005, 90: 1100.
[13] Melissa D L, Janice L B, Dyar M D. American Mineralogist, 2015, 100: 66.
[14] Bishop J L, Dyar M D. Lane M D, et al. International Journal of Astrobiology, 2005, 3: 275.
[15] Cloutis E A, Hawthome F C, Mertzman S A, et al. Icarus, 2006, 184: 121. |
[1] |
LIU Shu-hong1, 2, WANG Lu-si3*, WANG Li-sheng3, KANG Zhi-juan1, 2,WANG Lei1, 2,XU Lin1, 2,LIU Ai-qin1, 2. A Spectroscopic Study of Secondary Minerals on the Epidermis of Hetian Jade Pebbles From Xinjiang, China[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 169-175. |
[2] |
LIU Shu1, JIN Yue1, 2, SU Piao1, 2, MIN Hong1, AN Ya-rui2, WU Xiao-hong1*. Determination of Calcium, Magnesium, Aluminium and Silicon Content in Iron Ore Using Laser-Induced Breakdown Spectroscopy Assisted by Variable Importance-Back Propagation Artificial Neural Networks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3132-3142. |
[3] |
GUO Zhou-qian1, 2, LÜ Shu-qiang1, 2, HOU Miao-le1, 2*, SUN Yu-tong1, 2, LI Shu-yang1, 2, CUI Wen-yi1. Inversion of Salt Content in Simulated Mural Based on Hyperspectral
Mural Salt Index[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3272-3279. |
[4] |
WANG Lin, WANG Xiang*, ZHOU Chao, WANG Xin-xin, MENG Qing-hui, CHEN Yan-long. Remote Sensing Quantitative Retrieval of Chlorophyll a and Trophic Level Index in Main Seagoing Rivers of Lianyungang[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3314-3320. |
[5] |
LIU Liang-yu, YIN Zuo-wei*, XU Feng-shun. Spectral Characteristics and Genesis Analysis of Gem-Grade Analcime From Daye, Hubei[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2799-2804. |
[6] |
GAO Yu1, SUN Xue-jian1*, LI Guang-hua2, ZHANG Li-fu1, QU Liang2, ZHANG Dong-hui1, CHANG Jing-jing2, DAI Xiao-ai3. Study on the Derivation of Paper Viscosity Spectral Index Based on Spectral Information Expansion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2960-2966. |
[7] |
SONG Cheng-yang1, GENG Hong-wei1, FEI Shuai-peng2, LI Lei2, GAN Tian2, ZENG Chao-wu3, XIAO Yong-gui2*, TAO Zhi-qiang2*. Study on Yield Estimation of Wheat Varieties Based on Multi-Source Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2210-2219. |
[8] |
CAO Yue1, BAO Ni-sha1, 2*, ZHOU Bin3, GU Xiao-wei1, 2, LIU Shan-jun1, YU Mo-li1. Research on Remote Sensing Inversion Method of Surface Moisture Content of Iron Tailings Based on Measured Spectra and Domestic Gaofen-5 Hyperspectral High-Resolution Satellites[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1225-1233. |
[9] |
LAI Si-han1, LIU Yan-song1, 2, 3*, LI Cheng-lin1, WANG Di1, HE Xing-hui1, LIU Qi1, SHEN Qian4. Study on Hyperspectral Inversion of Rare-Dispersed Element Cadmium Content in Lead-Zinc Ores[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1275-1281. |
[10] |
HU Yi-bin1, BAO Ni-sha1, 2*, LIU Shan-jun1, 2, MAO Ya-chun1, 2, SONG Liang3. Research on Hyperspectral Features and Recognition Methods of Typical Camouflage Materials[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 297-302. |
[11] |
ZHANG Jian1, LIU Ya-jian2, CAO Ji-hu3. Raman Spectral Characteristics of Pyrite in Luyuangou Gold Deposit, Western Henan Province and Its Indicative Significance for Multiphase Metallogenesis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3770-3774. |
[12] |
ZHANG Chao1, 2, LIU Shan-jun1*, YI Wen-hua1, XIE Zi-chao2, LIU Bo-xiong2, YUE Heng1. Effect of Granularity on the Characteristics of Visible-Near Infrared Spectra of Different Coal Particles[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3858-3863. |
[13] |
ZHANG Li-qian1, 2, LIU Yang-jie2, 3. Comparative Study on Mineralogical Identification and Spectral
Characteristics of Four Iron-Containing Mineral Medicines[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2884-2889. |
[14] |
XU Liang-ji1, 2, MENG Xue-ying2, WEI Ren2, ZHANG Kun2. Experimental Research on Coal-Rock Identification Method Based on
Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(07): 2135-2142. |
[15] |
ZHU Meng-yuan1, 2, LÜ Bin1, 2*, GUO Ying2. Comparison of Haematite and Goethite Contents in Aeolian Deposits in Different Climate Zones Based on Diffuse Reflectance Spectroscopy and Chromaticity Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1684-1690. |
|
|
|
|