塑料激光诱导击穿光谱技术快速分类应用研究  

Fast Identification of Plastics with Laser-Induced Breakdown Spectroscopy

作　　者：孙倩倩[1] 杜敏[1] 郭连波[1] 郝中骐[1] 易荣兴 李嘉铭[1] 刘建国[1] 沈萌[1] 李祥友[1] 曾晓雁[1] 陆永枫[1] 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, Chin)

机构地区：[1]华中科技大学武汉光电国家实验室(筹)激光与太赫兹功能实验室,湖北武汉430074

出　　处：《光谱学与光谱分析》2017年第7期2205-2209,共5页Spectroscopy and Spectral Analysis

基　　金：中央高校基本科研业务费专项资金项目(2014QNRCO24;2015MS002)资助

摘　　要：在大气环境中,采用激光诱导击穿光谱技术与支持向量机算法相结合,对来自不同厂家不同颜色的20种工业塑料进行分类研究。首先对分类结果有影响的实验参数进行优化,在最佳的实验参数条件下进行光谱采集,采用6条非金属元素特征谱线,有效缩短了训练支持向量机分类模型所需时间,从而提高了塑料的分类效率。实验结果表明,利用碳、氢、氧、氮等主量非金属元素对这些工业塑料样品进行分类,测试集1 000个光谱数据中有996个识别正确,算术平均识别精度达到99.6%。在选取较少的主量非金属特征谱线的情况下,结合采用支持向量机算法,可以实现激光诱导击穿光谱技术对更多类型的塑料制品快速、高精度分类,为激光诱导击穿光谱技术在实现塑料分类方面提供了数据参考。Laser-induced breakdown spectroscopy（LIBS）combined with support vector machine（SVM）was adopted to identify20 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.6non-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 6non-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.

关 键 词：激光诱导击穿光谱技术 非金属元素特征谱线 支持向量机 塑料分类 

分 类 号：O657.3[理学—分析化学]