塑料激光诱导击穿光谱技术快速分类应用研究

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1000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 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 train-ing 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 1000 test spectra were identified correctly and the aver-age classification accuracy is reached to 99.6% .The classification efficiency is improved with 6 non-metallic characteristic spec-tral 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 effi-ciency .