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Laser & Optoelectronics Progress, Volume. 60, Issue 9, 0930002(2023)

Rock Identification Using LIBS Technique Combined with AFSA-SVM Algorithm

Chenhong Li1,2,3, Xinru Yan2,3,4, Yingjian Xin1,2,3, Huanzhen Ma2,3,4, Peipei Fang2,3,4, Hongpeng Wang1,2,5, and Xiong Wan1,2,4、*
Author Affiliations
  • 1Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
  • 2Key Laboratory of Space Active Opto-Electronics Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
  • 4Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, Zhejiang , China
  • 5College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (9)
    Equations (1)
    References (20)
    Cited By (5)
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    Figures & Tables(9)
    Schematic diagram of optical path of LIBS system of MarSCoDe

    Fig. 1. Schematic diagram of optical path of LIBS system of MarSCoDe

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    Average spectra of 32 samples obtained in 60 tests

    Fig. 2. Average spectra of 32 samples obtained in 60 tests

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    PCA analysis results of LIBS data of 15 types of rocks. (a) Contribution rate of each principal component and cumulative contribution rate; (b) three-dimensional scatter plot of top three principal components

    Fig. 3. PCA analysis results of LIBS data of 15 types of rocks. (a) Contribution rate of each principal component and cumulative contribution rate; (b) three-dimensional scatter plot of top three principal components

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    Schematic diagram of AFSA-SVM algorithm

    Fig. 4. Schematic diagram of AFSA-SVM algorithm

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    Schematic diagram of SVM classification principle

    Fig. 5. Schematic diagram of SVM classification principle

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    Convergence procedure and result of AFSA-SVM model. (a) Initialization state; (b), (c) convergence process; (d) convergence result

    Fig. 6. Convergence procedure and result of AFSA-SVM model. (a) Initialization state; (b), (c) convergence process; (d) convergence result

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    Results of AFSA-SVM, RF, BPANN and KNN algorithms in 10 consecutive times

    Fig. 7. Results of AFSA-SVM, RF, BPANN and KNN algorithms in 10 consecutive times

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    • Table 1. Sample number and categories of 32 national standard rocks

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      Table 1. Sample number and categories of 32 national standard rocks

      Category IDCategoryNational standard IDNo.
      1Igneous rock-syeniteGBW031251
      2Igneous rock-basaltGBW07105（GSR-3）2
      3Igneous rock-andesiteGBW07104（GSR-2）3
      4Igneous rock-pegmatiteGBW071254
      5Igneous rock-graniteGBW07121（GSR-14）5
      6Sedimentary-clay rockGBW07103（GSR-1）6
      GBW03121a7
      GBW031048
      7Sedimentary-chemical or biochemical rocksGBW07107（GSR-5）9
      GBW03107a10
      GBW0312311
      GBW0712712
      8Sedimentary-clastic rockGBW07217a13
      GBW0311214
      9Mixed polymetallic oreGBW07162（GSR-4）15
      GBW07106（GSO-1）16
      GBW07163（GSO-2）17
      GBW07164（GSO-3）18
      10Silver oreGBW07165（GSO-4）19
      GBW07255（GAg1）20
      GBW07256（GAg2）21
      GBW07257（GAg3）22
      GBW07259（GAg5）23
      GBW07260（GAg6）24
      11Nickel oreGBW0714625
      12Lead oreGBW0723526
      GBW0723627
      13Molybdenum stoneGBW0723928
      14Antimony oreGBW0728029
      15Gold oreGBW07242a（GAu-8a）30
      GBW07297a（GAu-19a）31
      GBW07299a（GAU-21A）32

    • Table 2. Performance comparison of different classification algorithms

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      Table 2. Performance comparison of different classification algorithms

      Classification algorithmAFSA-SVMRFBPANNKNN
      Train accuracy /%98.47100.0099.4098.47
      Test accuracy /%99.5695.6095.8090.17
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    Chenhong Li, Xinru Yan, Yingjian Xin, Huanzhen Ma, Peipei Fang, Hongpeng Wang, Xiong Wan. Rock Identification Using LIBS Technique Combined with AFSA-SVM Algorithm[J]. Laser & Optoelectronics Progress, 2023, 60(9): 0930002

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    Paper Information

    Category: Spectroscopy

    Received: Mar. 16, 2022

    Accepted: Apr. 18, 2022

    Published Online: May. 9, 2023

    The Author Email: Xiong Wan (wanxiong@mail.sitp.ac.cn)

    DOI:10.3788/LOP221020

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology