• Infrared and Laser Engineering
  • Vol. 50, Issue 5, 20200490 (2021)
Yanwei Yang1、2, Lili Zhang1、2, Xiaojian Hao2, and Ruizhong Zhang3
Author Affiliations
  • 1Department of Physics, Luliang University, Lvliang 033000, China
  • 2Key Laboratory of Instrumentation Science and Dynamic Measurement, North University of China, Taiyuan 030051, China
  • 3Shanxi Huaxing Aluminum Industry Co.Ltd., Lvliang 033603, China
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    DOI: 10.3788/IRLA20200490 Cite this Article
    Yanwei Yang, Lili Zhang, Xiaojian Hao, Ruizhong Zhang. Classification of iron ore based on machine learning and laser induced breakdown spectroscopy[J]. Infrared and Laser Engineering, 2021, 50(5): 20200490 Copy Citation Text show less
    References

    [1] Bo Zhang, Hong Min, Shu Liu, et al. X-Ray fluorescence spectroscopy combined with discriminant analysis to identify imported iron ore origin and brand: Application development. Spectroscopy and Spectral Analysis, 41, 258-291(2020).

    [2] Jinzhong Chen, Ruiling Ma, Zhenyu Chen, et al. Enhancement effect of carbon chamber confinement on laser plasma radiation. Optics and Precision Engineering, 21, 1942-1948(2013).

    [3] S U Choi, S C Han, J I Yun. Hydrogen isotopic analysis using molecular emission from laser-induced plasma on liquid and frozen water. Spectrochimica Acta Part B: Atomic Spectroscopy, 162, 105716(2019).

    [4] C Vanselow, D Stöbener, J Kiefer, et al. Revealing the impact of laser-induced breakdown on a gas flow. Measurement Science and Technology, 31, 027001(2019).

    [5] Yaguang Mei, Yuxin Cheng, Shusen Cheng, et al. Simultaneous analysis of Si, Mn and Ti segregation in pig iron by laser-induced breakdown spectroscopy. Infrared and Laser Engineering, 47, 0806003(2018).

    [6] Xianshuang Wang, Shuai Guo, Xiangjun Xu, et al. Fast recognition and classification of tetrazole compounds based on laser-induced breakdown spectroscopy and raman spectroscopy. Chinese Optics, 12, 888-895(2019).

    [7] Ang'ze Li, Xianshuang Wang, Xiangjun Xu, et al. Fast classi-fication of tobacco based on laser-induced breakdown spectroscopy. Chinese Optics, 12, 1139-1146(2019).

    [8] Yeqiu Li, Chenglin Sun, Qian Li, et al. Analysis of the heavy metals in atmospheric particulate matter using dual-pulsed laser-induced breakdown spectroscopy. Infrared and Laser Engineering, 48, 1005006(2019).

    [9] O Gazeli, E Bellou, D Stefas, et al. Laser-based classification of olive oils assisted by machine learning. Food Chemistry, 302, 1-7(2020).

    [10] Haobin Peng, Guohua Chen, Xiaoxian Chen, et al. Hybrid classification of coal and biomass by laser-induced breakdown spectroscopy combined with K-means and SVM. Plasma Science and Technology, 21, 64-72(2019).

    [11] D Diaz, D W Hahn, A Molina, et al. Evaluation of Laser-Induced Breakdown Spectroscopy (LIBS) as a measurement technique for evaluation of total elemental concentration in soils. Applied Spectroscopy, 66, 99-106(2012).

    [12] Xiaohui Li, Sibo Yang, Rongwei Fan, et al. Discrimination of soft tissues using laser-induced breakdown spectroscopy in combination with k nearest neighbors (kNN) and support vector machine (SVM) classifiers. Optics and Laser Technology, 102, 233-239(2018).

    [13] P Wang, N Li, C Yan, et al. Rapid quantitative analysis of the acidity of iron ore by laser-induced breakdown spectroscopy (LIBS) technique coupled with variable importance measurement-random forest (VIM-RF). Analytical Methods, 11, 1-10(2019).

    [14] Yun Zhao, M L Guindo, Xing Xu, et al. Deep learning associated with laser-induced breakdown spectroscopy (LIBS) for the prediction of lead in soil. Applied Spectroscopy, 73, 565-573(2019).

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    [1] Lin Fu, Yeqiu Li, Jia Zhen, Dehua Cheng, Qian Li, Qin Dai, Rina Wu. Spectral characteristics of laser-induced breakdown of organic explosives at low atmospheric pressure[J]. Infrared and Laser Engineering, 2022, 51(8): 20210720

    Yanwei Yang, Lili Zhang, Xiaojian Hao, Ruizhong Zhang. Classification of iron ore based on machine learning and laser induced breakdown spectroscopy[J]. Infrared and Laser Engineering, 2021, 50(5): 20200490
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