發(fā)布時(shí)間：2018-06-01 02:15

  本文選題：激光誘導(dǎo)擊穿光譜技術(shù) + 非金屬元素特征譜線　； 參考：《光譜學(xué)與光譜分析》2017年07期

【摘要】：在大氣環(huán)境中,采用激光誘導(dǎo)擊穿光譜技術(shù)與支持向量機(jī)算法相結(jié)合,對(duì)來自不同廠家不同顏色的20種工業(yè)塑料進(jìn)行分類研究。首先對(duì)分類結(jié)果有影響的實(shí)驗(yàn)參數(shù)進(jìn)行優(yōu)化,在最佳的實(shí)驗(yàn)參數(shù)條件下進(jìn)行光譜采集,采用6條非金屬元素特征譜線,有效縮短了訓(xùn)練支持向量機(jī)分類模型所需時(shí)間,從而提高了塑料的分類效率。實(shí)驗(yàn)結(jié)果表明,利用碳、氫、氧、氮等主量非金屬元素對(duì)這些工業(yè)塑料樣品進(jìn)行分類,測(cè)試集1 000個(gè)光譜數(shù)據(jù)中有996個(gè)識(shí)別正確,算術(shù)平均識(shí)別精度達(dá)到99.6%。在選取較少的主量非金屬特征譜線的情況下,結(jié)合采用支持向量機(jī)算法,可以實(shí)現(xiàn)激光誘導(dǎo)擊穿光譜技術(shù)對(duì)更多類型的塑料制品快速、高精度分類,為激光誘導(dǎo)擊穿光譜技術(shù)在實(shí)現(xiàn)塑料分類方面提供了數(shù)據(jù)參考。
[Abstract]:In the atmospheric environment, 20 kinds of industrial plastics from different manufacturers and different colors were classified and studied by combining laser induced breakdown spectroscopy with support vector machine (SVM). Firstly, the experimental parameters which have an effect on the classification results are optimized, and the spectral collection is carried out under the optimal experimental parameters, and six characteristic spectral lines of non-metallic elements are adopted, which effectively shortens the time required for training the classification model of support vector machine (SVM). Thus, the classification efficiency of plastics is improved. The experimental results show that 996 of the 1000 spectral data are correctly identified and the arithmetic average recognition accuracy is 99.6. The industrial plastics samples are classified by carbon, hydrogen, oxygen, nitrogen and other major nonmetallic elements. In the case of selecting fewer principal nonmetallic characteristic lines and combining with support vector machine (SVM) algorithm, laser induced breakdown spectroscopy can be used to classify more plastic products quickly and accurately. It provides a data reference for the classification of plastics by laser induced breakdown spectroscopy.
【作者單位】： 華中科技大學(xué)武漢光電國家實(shí)驗(yàn)室(籌)激光與太赫茲功能實(shí)驗(yàn)室;
【基金】：中央高�；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金項(xiàng)目(2014QNRCO24,2015MS002)資助
【分類號(hào)】：O657.319;TQ320.77

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本文編號(hào)：1962472