| 光谱学与光谱分析 |
|
|
|
|
|
| Near Infrared Spectroscopy of the Cretaceous Red Beds in Inner Mongolia Dongshengmiao |
| LIAO Yi-peng1, CAO Jian-jin1, 2*, WU Zheng-quan1, LUO Song-ying1, WANG Zheng-yang1 |
1. School of Earth Science and Geological Engineering, Sun Yat-sen University, Guangzhou 510275, China
2. Guangdong Key Laboratory of Geological Process and Mineral Resources Exploration, Guangzhou 510275, China |
|
|
|
|
Abstract Take the cores and surface weathered soil from the Cretaceous red beds in the western of Dongshengmiao mine of Inner Mongolia and analysis with near-infrared spectroscopy. The result shows that near-infrared spectroscopy can identify mineral quickly through the characteristic absorption peaks of each group. The Cretaceous red beds in the western of Dongshengmiao mine is argillaceous cementation, it is mainly composed of quartz, feldspar, montmorillonite, illite, chlorite, muscovite etc, the mineral composition is mainly affected by the upstream source area. The clay mineral like montmorillonite water swelling and uneven drying shrinkage expands the original crack and creates new cracks, reduces its strength, which is the mainly reason of its disintegration. According to the composition of clay mineral, we speculate its weathering process is mainly physical weathering, the climate during the weathering is cold and dry. The results can not only improve the geological feature of the mining area, but also show that the near-infrared spectroscopy technology can analyze the mineral composition of soil and rock effectively on the basis of Mineral spectroscopy, which demonstrates the feasibility of the near-infrared spectroscopy can analyze minerals in soil and rock quickly, that shows the feasibility in geology study, provides new ideas for the future research of soil and rock.
|
|
Received: 2014-06-23
Accepted: 2014-09-16
|
|
|
|
Corresponding Authors:
CAO Jian-jin
E-mail: eescjj@mail.sysu.edu.cn
|
|
[1] PENG Bo-xing, LIU Ying-jiong, LIU Yi(彭柏兴，刘颖炯，刘 毅). Chinese Journal of Geotechnical Engineering(岩土工程学报)，2011，(S1): 148.
[2] ZHANG Jun-yun, ZHOU De-pei(张俊云，周德培). Journal of Southwest Jiaotong University(西南交通大学学报)，2006，(01): 74.
[3] GUO Yong-chun, XIE Qiang, WEN Jiang-quan,(郭永春，谢 强，文江泉). Hydrogeology & Engineering Geology(水文地质工程地质)，2007，(06): 67.
[4] CHEN Jun, WANG Zi-gao, ZENG Xian-qiang, et al(陈 军，王自高，曾宪强，等). Water Power(水力发电)，2006，(11): 31.
[5] ZHONG Kai, LIU Ai-ping, XIE Qiang(钟 凯，刘爱萍，谢 强). Subgrade Engineering(路基工程)，2000，(04): 53.
[6] CAO Jian-jin, LIANG Zhi-rong, LIU Ke-xing, et al(曹建劲，梁致荣，刘可星，等). Progress in Natural Science(自然科学进展)，2004，(07): 107.
[7] QIAN Yu-lin, ZHANG Yang(钱玉麟，张 洋). Industrial Minerals & Processing(化工矿物与加工), 2011，(01): 25.
[8] XIU Lian-cun, ZHENG Zhi-zhong, YU Zheng-kui, et al(修连存，郑志忠，俞正奎，等). Acta Geologica Sinica(地质学报), 2007, (11): 1584.
[9] WU Zheng-quan, CAO Jian-jin, WEI Xiao-jun, et al(吴政权，曹建劲，韦潇君, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2013, 33(10): 2666.
[10] Hebei Geological College, Inner Mongolia Chemical Geological Team(河北地质学院, 内蒙古化工地质队). Journal of Shijiazhuang University of Economics(河北地质学院学报)，1980，2: 47.
[11] PENG Run-min, DI Yu-sheng, HAN Xue-feng, et al(彭润民，翟裕生，韩雪峰，等). Acta Petrologica Sinica(岩石学报)，2007，3: 679.
[12] MENG Kai, SHEN Jun-feng, QIN Min, et al(孟 恺，申俊峰，卿 敏，等). Bulletin of Mineralogy, Petrology and Geochemistry(矿物岩石地球化学通报)，2009，(02): 147.
[13] BAI Li-xin( 白立新). Ningxia Engineering Technology(宁夏工程技术), 2007, (4)：344.
[14] MIU Yuan-xing, RAN Chong-ying(缪远兴，冉崇英). Geochimica(地球化学)，1992，(04): 375.
[15] XIU Lian-cun, ZHENG Zhi-zhong, YU Zheng-kui, et al(修连存，郑志忠，俞正奎，等). Roch and Mineral Analysis(岩矿测试), 2009, (6): 519.
[16] LUO Jia-xian( 罗家贤). Acta Pedologica Sinica(土壤学报), 1990, (04): 385.
[17] CAO Ke, LI Xiang-hui, WANG Cheng-shan(曹 珂，李祥辉，王成善). Acta Geologica Sinica(地质学报)，2008, 82(1): 115.
[18] LAN Xian-hong(蓝先洪). Geological Science and Technology Information(地质科技情报), 1990, (04): 31.
[19] CHENG Jie, TANG De-xiang, ZHANG Xu-jiao, et al(程 捷，唐德翔，张绪教，等). Geoscience(现代地质)，2003，(1): 47. |
| [1] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
| [2] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [3] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
| [4] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
| [5] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
| [6] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
| [7] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
| [8] |
ZHANG Shu-fang1, LEI Lei2, LEI Shun-xin2, TAN Xue-cai1, LIU Shao-gang1, YAN Jun1*. Traceability of Geographical Origin of Jasmine Based on Near
Infrared Diffuse Reflectance Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3389-3395. |
| [9] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
| [10] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
| [11] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
| [12] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
| [13] |
HUANG Hua1, LIU Ya2, KUERBANGULI·Dulikun1, ZENG Fan-lin1, MAYIRAN·Maimaiti1, AWAGULI·Maimaiti1, MAIDINUERHAN·Aizezi1, GUO Jun-xian3*. Ensemble Learning Model Incorporating Fractional Differential and
PIMP-RF Algorithm to Predict Soluble Solids Content of Apples
During Maturing Period[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3059-3066. |
| [14] |
CHEN Jia-wei1, 2, ZHOU De-qiang1, 2*, CUI Chen-hao3, REN Zhi-jun1, ZUO Wen-juan1. Prediction Model of Farinograph Characteristics of Wheat Flour Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3089-3097. |
| [15] |
GUO Ge1, 3, 4, ZHANG Meng-ling3, 4, GONG Zhi-jie3, 4, ZHANG Shi-zhuang3, 4, WANG Xiao-yu2, 5, 6*, ZHOU Zhong-hua1*, YANG Yu2, 5, 6, XIE Guang-hui3, 4. Construction of Biomass Ash Content Model Based on Near-Infrared
Spectroscopy and Complex Sample Set Partitioning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3143-3149. |
|
|
|
|
