Spectroscopy and Spectral Analysis, Volume. 37, Issue 7, 2205(2017)

Fast Identification of Plastics with Laser-Induced Breakdown Spectroscopy

SUN Qian-qian*, DU Min, GUO Lian-bo, HAO Zhong-qi, YI Rong-xing, LI Jia-ming, LIU Jian-guo, SHEN Meng, LI Xiang-you, ZENG Xiao-yan, and LU Yong-feng
Author Affiliations
  • [in Chinese]
  • show less

    Laser-induced breakdown spectroscopy (LIBS) combined with support vector machine (SVM) was adopted to identify 20 kinds of different colored industrial plastics from different manufacturers in open air. The experimental parameters of spectral acquisition were optimized firstly. 100 spectra recorded under optimum conditions were randomly and equally divided into training set and test set. 6 non-metallic characteristic spectral lines were used to avoid the interference with metallic lines. And the training time of SVM model was reduced. The results show that 996 of 1 000 test spectra were identified correctly and the average classification accuracy is reached to 996%. The classification efficiency is improved with 6 non-metallic characteristic spectral lines. The research demonstrates that, when fewer of major non-metallic characteristic spectral lines are used, laser-induced breakdown spectroscopy technique with support vector machine can identify more kinds of plastics with high accuracy and efficiency.

    Tools

    Get Citation

    Copy Citation Text

    SUN Qian-qian, DU Min, GUO Lian-bo, HAO Zhong-qi, YI Rong-xing, LI Jia-ming, LIU Jian-guo, SHEN Meng, LI Xiang-you, ZENG Xiao-yan, LU Yong-feng. Fast Identification of Plastics with Laser-Induced Breakdown Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2017, 37(7): 2205

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Received: Mar. 14, 2016

    Accepted: --

    Published Online: Aug. 30, 2017

    The Author Email: Qian-qian SUN (jessiesun211@163.com)

    DOI:10.3964/j.issn.1000-0593(2017)07-2205-05

    Topics