Open AccessIdentification of plastics by laser-induced breakdown spectroscopy combined with support vector machine algorithm
Author(s) -
Yu Yang,
Hao Zeng,
Changmao Li,
Lianbo Guo,
Kuohu Li,
Zeng Qing-Dong,
Xiangyou Li,
Ren Zhao,
Xiaoyan Zeng
Publication year - 2013
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.62.215201
Subject(s) - laser induced breakdown spectroscopy , support vector machine , spectroscopy , training set , spectral line , set (abstract data type) , materials science , laser , identification (biology) , test set , data set , algorithm , spectrometer , computer science , analytical chemistry (journal) , artificial intelligence , optics , physics , chemistry , chromatography , botany , quantum mechanics , biology , astronomy , programming language
Laser-induced breakdown spectroscopy (LIBS) combined with support vector machine (SVM) algorithm was used to identify 11 kinds of plastics. For each plastic, 100 spectra recorded by the spectrometer system were divided equally into training set and test set, and the former was used to train SVM model while the latter was used to validate SVM model created by the training set. Result shows that 543 of 550 test set spectra are identified correctly with the average correct identification rate 98.73%. However, there are six spectra of PU misidentified as PMMA. This is because the difference of nitrogen content in 11 plastics cannot be reflected by the intensities of N I 746.87 nm and C-N (0,0) 388.3 nm due to the influence of ambient air. Methods and reference data are provided for further study of plastics identification by laser-induced breakdown spectroscopy technique.