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| 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, LU Yong-feng |
| Wuhan National Laboratory for Optoelectronics, Laser and Terahertz Technology Division, Huazhong University of Science and Technology, Wuhan 430074, China |
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Abstract 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.
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Received: 2016-03-14
Accepted: 2016-08-12
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Corresponding Authors:
LI Xiang-you
E-mail: xyli@mail.hust.edu.cn
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[1] Anzano J, Casanova M E, Bermúdez M S，et al. Polymer Testing, 2006, 25: 623.
[2] Coltro L, Duarte L C. Polímeros, 2013, 23(1): 128.
[3] Siddiqui M N, Gondal M A, Redhwi H H. Journal of Environmeatal Science and Health Part A, 2008, 43: 1303.
[4] Anzano!J M, Gornushkin I B, Smith B W, et al. Polymer Engineering and Science, 2000, 40(11): 2423.
[5] Rios P, Stuart J A, Grant E. Environmental Science and Technology, 2003, 37: 5463.
[6] Van Den Broek W H A M, Wienke D, Melssen W J, et al. Analytica Chimica Acta, 1998, 361: 161.
[7] Dinger P. BioCycle: Journal of Composting & Organics Recycling, 1992, 33: 88.
[8] Chanda M, Roy S K. Plastics Technology Handbook 4<sup>th</sup> Edn, New York: Marcel Dekker, 1997.
[9] YANG Ming-tai, ZHANG Lian-ping(杨明太，张连平). Nuclear Electronics & Detection Technology, 2008, 28(5): 1008.
[10] Allen V, Kalivas J H, Rodriguez R G. Applied Spectroscopy, 1999, 53(6): 672.
[11] Zheng Peichao, Shi Minjie, Wang Jinmei, et al. Plasma Science and Technology, 2015, 17 (8): 664.
[12] Noll R. Laser-Induced Breakdown Spectroscopy: Fundamentals and Applications. Berlin Heidelberg: Springer-Verlag, 2012.
[13] Wang Zhe, Yuan Tiangbi, Hou Zongyuan, et al. Frontiers of Physics, 2014, 9(4): 419.
[14] Li Changmao, Guo Lianbo, Hao Zhongqi, et al. Journal of Analytical Atomic Spectrometry, 2014, 29(4): 638.
[15] Barthélemy O, Margot J, Laville S, et al. Applied Spectroscopy, 2005, 59(4): 529.
[16] WANG Xu-zhao, HAO Zhong-qi, GUO Lian-bo, et al(王旭朝，郝中骐，郭连波，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2015, 35(5): 1159.
[17] Boueri M, Motto-Ros V, Lei Weiqi, et al. Applied Spectroscopy, 2011, 65(3): 307.
[18] Banaee M, Tavassoli S H. Polymer Testing, 2012, 31(6): 759.
[19] Yu Yang, Guo Lianbo, Hao Zhongqi, et al. Optics Express, 2014, 22(4): 3895. |
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