• Core Journal of China
  • DOAJ
  • Scopus
  • Chinese Scientific and Technical Papers and Citations (CSTPC)
  • Chinese Science Citation Database (CSCD)
GAO Qiyun,ZHOU Li,YI Zebang,et al. Effect of Granularity on the Characteristic Visible-Near Infrared Spectra of Karst-Type Bauxite[J]. Rock and Mineral Analysis,2024,43(2):234−246. DOI: 10.15898/j.ykcs.202308090133
Citation: GAO Qiyun,ZHOU Li,YI Zebang,et al. Effect of Granularity on the Characteristic Visible-Near Infrared Spectra of Karst-Type Bauxite[J]. Rock and Mineral Analysis,2024,43(2):234−246. DOI: 10.15898/j.ykcs.202308090133

Effect of Granularity on the Characteristic Visible-Near Infrared Spectra of Karst-Type Bauxite

More Information
  • Received Date: August 08, 2023
  • Revised Date: March 11, 2024
  • Accepted Date: March 15, 2024
  • Available Online: April 28, 2024
  • HIGHLIGHTS
    (1) The reflectivity of bauxite (bauxite-bearing rock) block samples exceeds 14% in the entire wavelength range, and the highest reflectivity of granular samples exceeds 28%.
    (2) As the particle size decreases, the spectral reflectance of bauxite (bauxite-bearing rock) gradually increases, and its reflective spectral morphology is similar.
    (3) Bauxite and bauxite-bearing rock can be distinguished by characteristic spectra of small particle powder samples at wavelengths of 1800nm, 1900nm, 2160nm, and 2200nm.

    The reflection spectrum of rocks and minerals is an important reference for intelligent perception technology and remote sensing information recognition in intelligent mining. Particle size is one of the important factors affecting the reflection spectral characteristics of rocks and minerals. In order to reveal the reflection spectral characteristics of karst type bauxite with different particle sizes, the influence of particle size on the visible and near-infrared spectra of karst type bauxite is elucidated. In the study, the visible light near-infrared reflectance spectra of bauxite (bauxite-bearing rock) samples with different particle sizes were measured using the ASD FieldSpec-4 spectrophotometer. Bauxite and bauxite-bearing rock can be distinguished by characteristic spectra of small particle powder samples at wavelengths of 1800nm, 1900nm, 2160nm, and 2200nm. The research results indicate that as the particle size decreases, the spectral reflectance gradually increases. The BRIEF REPORT is available for this paper at http://www.ykcs.ac.cn/en/article/doi/10.15898/j.ykcs.202308090133.

    BRIEF REPORT
    Significance: Aluminum is one of the most widely used metals in the world, and bauxite is the main raw material for producing metallic aluminum[30-31]. The use of hyperspectral remote sensing for rock and mineral exploration has gradually gained attention and become a key issue in the construction of intelligent mines[1-2]. Studying the reflection spectral characteristics can quickly identify bauxite, which is beneficial for improving the reliability and precision of mineral information extraction. ASD FieldSpec-4 ground object spectrometer is used to study the visible near-infrared reflection spectral characteristics of bauxite (bauxite-bearing rock) samples under different particle size conditions. In the analysis results, the spectral differences between bauxite and bauxite-bearing rock are discussed, providing data support for the establishment of bauxite spectrum database and intelligent recognition. The results indicate that there is a significant difference in the reflection spectral characteristics between bauxite and bauxite-bearing rock, which can be distinguished by the reflection spectral characteristics.
    Methods: The visible and near-infrared reflectance spectra of bauxite (bauxite-bearing rock) samples were tested by the ASD FieldSpec-4 portable ground object spectrometer (USA). The samples used were XSB-1, XSB-2, XSB-3, XSB-4, XSB-5, and XSB-6, each with a particle size of 9 levels: 2−3mm, 1−2mm, 0.60−1mm, 0.30−0.60mm, 0.20−0.30mm, 0.08−0.20mm, 0.065−0.08mm, 0.04−0.065mm, <0.04mm. Different particle size powder samples were tested in a dark room. The chemical composition of Al2O3, SiO2, Fe2O3, etc. of bauxite (bauxite-bearing rock) samples was determined by X-ray fluorescence spectrometry (XRF); the mineral composition of bauxite (bauxite-bearing rock) samples was determined by X-ray powder diffraction (XRD). The commonalities and differences in reflectance spectra of bauxite (bauxite-bearing rock) with different particle sizes were analyzed. Combining the results of major element content and mineral composition, the intrinsic mechanism of bauxite and bauxite-bearing rock was analyzed.
    Data and Results: Xiaoshanba bauxite (bauxite-bearing rock) exhibits significantly different spectral characteristics due to different mineral compositions, among which the reflection spectral characteristics of bauxite are mainly consistent with those of monohydrate alumina, with obvious trough characteristics at wavelengths of 1400nm and 1800nm, caused by OH vibration bands. The reflection spectral characteristics of bauxite-bearing rocks are mainly consistent with kaolinite, with significant trough characteristics at wavelengths of 1400nm, 1900nm, 2160nm, and 2200nm, respectively, caused by the combination of OH frequency doubling, H2O vibration band, and Al-O-H bending fundamental harmonic vibration, and exhibit double absorption and absorption peaks in the 2160−2200nm wavelength range. The overall reflectivity of bauxite (bauxite-bearing rock) samples with different particle sizes is relatively high, with the highest reflectivity of block samples exceeding 14% in the entire wavelength band and the highest reflectivity of granular samples exceeding 28%, where the trend of change is basically the same. As the particle size increases from <0.04mm to 3mm, the reflectivity of both bauxite and bauxite-bearing rock gradually decreases, and the overall absorption intensity of bauxite characteristic valleys is relatively stable, while the absorption intensity of bauxite-bearing rock characteristic valleys shows a gradually decreasing trend.
  • [1]
    刘善军, 王东, 毛亚纯, 等. 智能矿山中的岩矿光谱智能感知技术与研究进展[J]. 金属矿山, 2021(7): 1−15.

    Liu S J, Wang D, Mao Y C, et al. Intelligent spectrum sensing technology and research progress of rock and ore in intelligent mine[J]. Metal Mine, 2021(7): 1−15.
    [2]
    张瑞新, 毛善君, 赵红泽, 等. 智慧露天矿山建设基本框架及体系设计[J]. 煤炭科学技术, 2019, 47(10): 1−23.

    Zhang R X, Mao S J, Zhao H Z, et al. Framework and structure design of system construction for intelligent open-pit mine[J]. Coal Science and Technology, 2019, 47(10): 1−23.
    [3]
    刘新星, 张弘, 张娟, 等. 基于红外光谱技术研究内蒙古乌奴格吐山斑岩铜钼矿蚀变和矿化特征[J]. 岩矿测试, 2021, 40(1): 121−133.

    Liu X X, Zhang H, Zhang J, et al. A study on alteration mineral assemblages and mineralization characteristics of a Wunugetushan porphyry copper-molybdenum deposit in Inner Mongolia, China based on infrared spectroscopy[J]. Rock and Mineral Analysis, 2021, 40(1): 121−133.
    [4]
    张永磊, 陶奇, 何宏平, 等. 近红外光谱对岩矿表面黏土矿物覆层的响应[J]. 地球化学, 2023, 52(1): 41−52.

    Zhang Y L, Tao Q, He H P, et al. Response of near-infrared spectra to clay coatings on mineral surface[J]. Geochimica, 2023, 52(1): 41−52.
    [5]
    郭东旭, 刘晓, 张海兰, 等. 基于红外光谱技术研究云南普朗斑岩铜矿的蚀变和矿化特征[J]. 岩矿测试, 2021, 40(5): 698−709.

    Guo D X, Liu X, Zhang H L, et al. The infrared spectroscopy characteristics of alteration and mineralization in the porphyry copper deposit in Pulang, Yunnan Province[J]. Rock and Mineral Analysis, 2021, 40(5): 698−709.
    [6]
    张博, 司庆红, 苗培森, 等. 基于近红外岩心光谱扫描技术研究鄂尔多斯盆地彭阳铀矿床矿物分布特征[J]. 岩矿测试, 2022, 41(5): 733−743.

    Zhang B, Si Q H, Miao P S, et al. Mineral distribution characteristics of the Pengyang uranium deposit based on near infrared core spectral scanning technology[J]. Rock and Mineral Analysis, 2022, 41(5): 733−743.
    [7]
    代晶晶, 王登红, 代鸿章, 等. 川西甲基卡锂矿基地典型岩石及矿物反射波谱特征研究[J]. 岩矿测试, 2018, 37(5): 507−517.

    Dai J J, Wang D H, Dai H Z, et al. Reflectance spectral characteristics of rocks and mineral in Jiajika lithium deposits in West Sichuan[J]. Rock and Mineral Analysis, 2018, 37(5): 507−517.
    [8]
    代晶晶, 王登红, 令天宇. 基于地面反射波谱技术的锂含量定量反演研究[J]. 遥感技术与应用, 2019, 34(5): 992−997.

    Dai J J, Wang D H, Ling T Y. Quantitative estimation of content of lithium using reflectance spectroscopy[J]. Remote Sensing Technology and Application, 2019, 34(5): 992−997.
    [9]
    韩海辉, 任广利, 张转, 等. 北山方山口地区典型蚀变岩矿的光谱特征研究[J]. 西北地质, 2018, 51(4): 263−273.

    Han H H, Ren G L, Zhang Z, et al. Spectral characteristics of typical altered rocks and minerals from Fangshankou area in Beishan[J]. Northwestern Geology, 2018, 51(4): 263−273.
    [10]
    Tan W, Qin X R, Liu J, et al. Visible/near infrared reflectance (VINR) spectral features of ion-exchangeable rare earth elements hosted by clay minerals: Potential use for exploration of regolith-hosted REE deposits[J]. Applied Clay Science, 2021, 215: 106320. doi: 10.1016/j.clay.2021.106320
    [11]
    Tan W, Qin X R, Liu J, et al. Feasibility of visible short-wave infrared reflectance spectroscopy to characterize regolith-hosted rare earth element mineralization[J]. Economic Geology, 2022, 117(2): 495−508. doi: 10.5382/econgeo.4877
    [12]
    Turner D J, Rivard B, Groat L A. Visible and short-wave infrared reflectance spectroscopy of selected REE-bearing silicate minerals[J]. American Mineralogist: Journal of Earth and Planetary Materials, 2018, 103(6): 927−943. doi: 10.2138/am-2018-6195
    [13]
    Amer R, El Mezayen A, Hasanein M. ASTER spectral analysis for alteration minerals associated with gold mineralization[J]. Ore Geology Reviews, 2016, 75: 239−251. doi: 10.1016/j.oregeorev.2015.12.008
    [14]
    燕守勋, 张兵, 赵永超, 等. 矿物与岩石的可见-近红外光谱特性综述[J]. 遥感技术与应用, 2003, 18(4): 191−201.

    Yan S X, Zhang B, Zhao Y C, et al. Summarizing the vis-NIR spectra of minerals and rocks[J]. Remote Sensing Technology and Application, 2003, 18(4): 191−201.
    [15]
    盛洁, 刘展, 曾齐红, 等. 基于高光谱的砂岩露头孔隙度估算方法[J]. 红外与毫米波学报, 2018, 37(6): 775−783, 789.

    Sheng J, Liu Z, Zeng Q H, et al. Porosity estimation method in sandstone outcrop based on hyper-spectrum[J]. Journal of Infrared and Millimeter Waves, 2018, 37(6): 775−783, 789.
    [16]
    王润生, 熊盛青, 聂洪峰, 等. 遥感地质勘查技术与应用研究[J]. 地质学报, 2011, 85(11): 1699−1743.

    Wang R S, Xiong S Q, Nie H F, et al. Remote sensing technology and its application geological exploration acta[J]. Acta Geologica Sinica, 2011, 85(11): 1699−1743.
    [17]
    甘甫平, 王润生, 马蔼乃, 等. 光谱遥感岩矿识别基础与技术研究进展[J]. 遥感技术与应用, 2002, 17(3): 140−147.

    Gang F P, Wang R S, Ma A N, et al. The development and tendency of both basis and techniques of discrimination for minerals and rocks using spectral remote sensing data[J]. Remote Sensing Technology and Application, 2002, 17(3): 140−147.
    [18]
    汪金花, 曹兰杰, 白洋, 等. 铁尾矿粒径和湿度因子对高光谱特征参量影响[J]. 矿产综合利用, 2019, 40(2): 128−133.

    Wang J H, Cao L J, Bai Y, et al. Influence of iron tailings’ particle size and humidity factor on hyperspectral characteristic parameters[J]. Multipurpose Utilization of Mineral Resources, 2019, 40(2): 128−133.
    [19]
    王润生. 遥感地质技术发展的战略思考[J]. 国土资源遥感, 2008(1): 1−12, 42.

    Wang R S. On the development strategy of remote sensing technology in geology[J]. Remote Sensing for Land & Resources, 2008(1): 1−12, 42.
    [20]
    闫柏琨, 陈伟涛, 王润生, 等. 基于Hapke模型的矿物红外发射光谱随粒度与发射角的变异规律[J]. 地球科学——中国地质大学学报, 2009, 34(6): 946−954. doi: 10.3799/dqkx.2009.108

    Yan B K, Chen W T, Wang R S, et al. Variation law of mineral emissivity spectra with mineral granularity and emission angle based on Hapke model[J]. Earth Science—Journal of China University of Geosciences, 2009, 34(6): 946−954. doi: 10.3799/dqkx.2009.108
    [21]
    Salisbury J W, Wald A. The role of volume scattering in reducing spectral contrast of reststrahlen bands in spectra of powdered minerals[J]. Icarus, 1992, 96(1): 121−128. doi: 10.1016/0019-1035(92)90009-V
    [22]
    Okin G S, Painter T H. Effect of grain size on remotely sensed spectral reflectance of sandy desert surfaces[J]. Remote Sensing of Environment, 2004, 89(3): 272−280. doi: 10.1016/j.rse.2003.10.008
    [23]
    杨柏林, 王兴理, 王忠圣. 岩石和矿物的反射光谱特征及其应用[J]. 地球化学, 1987(1): 89−96.

    Yang B L, Wang X L, Wang Z S. Reflective spectrum features of rocks and ores and their application[J]. Geochimica, 1987(1): 89−96.
    [24]
    王东, 刘善军, 祁玉馨, 等. 颗粒度对鞍山式铁矿反射光谱特征的影响研究[J]. 光谱学与光谱分析, 2021, 41(5): 1513−1518.

    Wang D, Liu S J, Qi Y X, et al. Effect of particle size on reflectance spectra of Anshan iron ore[J]. Spectroscopy and Spectral Analysis, 2021, 41(5): 1513−1518.
    [25]
    刘海琪, 刘善军, 丁瑞波. 颗粒度对高品位赤铁矿可见光-近红外光谱的影响研究[J]. 金属矿山, 2022(4): 158−162.

    Liu H Q, Liu S J, Ding R B. Effect of particle size on visible-near infrared spectral of high grade Hematite[J]. Metal Mine, 2022(4): 158−162.
    [26]
    王延霞, 吴见, 周亮广, 等. 不同粒度条件下矿物光谱变化分析[J]. 光谱学与光谱分析, 2015, 35(3): 803−808.

    Wang Y X, Wu J, Zhou L G, et al. Mineral spectrum change analysis under the conditions of different particle size[J]. Spectroscopy and Spectral Analysis, 2015, 35(3): 803−808.
    [27]
    杨恩, 王世博, 葛世荣. 典型煤系岩石的可见-近红外光谱特征研究[J]. 工矿自动化, 2019, 45(3): 45−51, 89.

    Yang E, Wang S B, Ge S R. Research on visible-near infrared spectrum features of typical coal measures rocks[J]. Industry and Mine Automation, 2019, 45(3): 45−51, 89.
    [28]
    张超, 刘善军, 易文华, 等. 颗粒度对不同煤种可见光-近红外光谱的影响[J]. 光谱学与光谱分析, 2022, 42(12): 3858−3863.

    Zhang C, Liu S J, Yi W H, et al. 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.
    [29]
    Zhuang Y, Zhang H, Ma P, et al. Visible and near-infrared reflectance spectra of igneous rocks and their powders[J]. Icarus, 2023, 391: 115346. doi: 10.1016/j.icarus.2022.115346
    [30]
    王庆飞, 刘学飞, 杨淑娟, 等. 喀斯特型铝土矿是如何形成的?[J]. 地球科学, 2022, 47(10): 3880−3881.

    Wang Q F, Liu X F, Yang S J, et al. How is karst bauxite formed?[J]. Earth Science, 2022, 47(10): 3880−3881.
    [31]
    杜远生, 余文超. 沉积型铝土矿的陆表淋滤成矿作用: 兼论铝土矿床的成因分类[J]. 古地理学报, 2020, 22(5): 812−826.

    Du Y S, Yu W C. Subaerial leaching process of sedimentary bauxite and the discussion on classifications of bauxite deposits[J]. Journal of Palaeogeography, 2020, 22(5): 812−826.
    [32]
    张生, 何卫军, 文明, 等. 近红外光谱分析方法在桂西地区沉积型铝土矿找矿中的研究[J]. 化工矿产地质, 2023, 45(1): 58-65.

    Zhang S, He W J, Wen M, et al. Study on near infrared spectroscopy in sedimentary bauxite in Western Guangxi[J]. Geology of Chemical Minerals, 2022, 45(4): 58-65.
    [33]
    Thorsos E I. The validity of the Kirchhoff approximation for rough surface scattering using a Gaussian roughness spectrum[J]. The Journal of Acoustical Society of America, 1988, 83(1): 78−92. doi: 10.1121/1.396188
    [34]
    徐林刚, 孙莉, 孙凯. 中国铝土矿的成矿规律、关键科学问题与研究方法[J]. 矿床地质, 2023, 42(1): 22−40.

    Xu L G, Sun L, Sun K. Metallogenic regularity, key scientific problems and research methods of bauxite in China[J]. Mineral Deposits, 2023, 42(1): 22−40.
    [35]
    叶霖, 程曾涛, 潘自平. 贵州修文小山坝铝土矿中稀土元素地球化学特征[J]. 矿物岩石地球化学通报, 2007, 26(3): 228−233.

    Ye L, Cheng Z T, Pan Z P. The REE geochemical characteristics of the Xiaoshanba bauxite deposit, Guizhou[J]. Bulletin of Mineralogy, Petrology and Geochemistry, 2007, 26(3): 228−233.
    [36]
    兰永文, 王洪雨, 栗欢欢. 贵州修文小山铝土矿床地质特征及其成因探讨[J]. 西部探矿工程, 2015, 27(8): 171−175.

    Lan Y W, Wang H Y, Li H H. Geological characteristics and genesis of Xiaoshan bauxite deposit in Xiuwen, Guizhou[J]. West-China Exploration Engineering, 2015, 27(8): 171−175.
    [37]
    陈群, 戴晓燕, 梁鹏, 等. 贵州省修文县石炭系小山坝铝土矿矿床地质特征[J]. 贵州地质, 2019, 36(4): 316−323.

    Chen Q, Dai X Y, Liang P, et al. Geological characteristics of Xiaoshanba bauxite deposit in carboniferous system of Xiuwen, Guizhou[J]. Guizhou Geology, 2019, 36(4): 316−323.
    [38]
    窦增文. 西南地区某高泥堆积型铝土矿选矿试验研究[J]. 金属矿山, 2022(7): 193−197.

    Dou Z W. Experimental study on beneficiation of a high mud accumulation type bauxite in southwestern district[J]. Metal Mine, 2022(7): 193−197.
    [39]
    黄国智, 方启学, 石伟, 等. 放粗铝土矿选矿精矿粒度的可行性研究[J]. 轻金属, 2000(7): 7−10.

    Huang G Z, Fang Q X, Shi W, et al. Feasibility study of enlarging the coarseness of bauxite concentrate[J]. Light Metals, 2000(7): 7−10.
    [40]
    李沛刚, 王登红, 赵芝, 等. 贵州大竹园铝土矿矿床地质、地球化学与成矿规律[M]. 北京: 科学出版社, 2014: 1-217.

    Li P G, Wang D H, Zhao Z, et al. Geology, geochemistry and metallogenic regularity of Dazhuyuan bauxite deposit in Guizhou Province[M]. Beijing: Science Press, 2014: 1-217.
    [41]
    曹信禹. 岩溶堆积型铝土矿工业指标的初步探讨[J]. 轻金属, 1984(9): 1−4.

    Cao X Y. Preliminary discussion on industrial index of karst accumulation bauxite[J]. Light Metals, 1984(9): 1−4.
    [42]
    秦效荣, 姚玉增, 何宏平, 等. 广东梅州花岗岩风化壳剖面的可见光-短波红外反射光谱特征及其对风化强度的指示[J]. 地球化学, 2020, 49(4): 422−434.

    Qin X R, Yao Y Z, He H P, et al. Visible to shortwave-infrared spectroscopic characteristics and weathering intensity indicators of a weathering-crust-type REE deposit in granite bedrock, from Meizhou, Guangdong Province[J]. Geochimica, 2020, 49(4): 422−434.
    [43]
    代晶晶, 王润生. 常见透明矿物类波谱特征研究综述[J]. 地质科技情报, 2013, 32(2): 8−14.

    Dai J J, Wang R S. Spectral characteristics of typical transparent mineral groups[J]. Geological Science and Technology Information, 2013, 32(2): 8−14.
    [44]
    Clark R N. Spectroscopy of Rocks and Minerals, and Principles of Spectroscopy[M]//Manual of Remote Sensing. New York: Remote Sensing for the Earth Sciences, 1999: 3–58.
    [45]
    Vernazza P, Carry B, Emery J, et al. Mid-infrared spectral variability for compositionally similar asteroids: Implications for asteroid particle size distributions[J]. Icarus, 2010, 207(2): 800−809. doi: 10.1016/j.icarus.2010.01.011

Catalog

    Article views (105) PDF downloads (21) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return