LIBS技术结合多元校正定标检测土壤中的Cr

发布时间：2018-04-12 18:15

本文选题：激光诱导击穿光谱 + 土壤　；参考：《光谱学与光谱分析》2016年06期

【摘要】：激光诱导击穿光谱(LIBS)技术结合支持向量机(SVM)定量分析土壤中Cr元素的含量。利用波长为1 064nm的Nd∶YAG脉冲激光器作为激发光源,采用光栅光谱仪和CCD分光探测不同重金属元素含量土壤样品的LIBS特征光谱。为了提高土壤中Cr元素定量分析的精度,分别采用多元线性回归分析和SVM两种方法对土壤中Cr元素的含量进行定量分析。研究结果表明,采用多元线性回归分析方法可以有效提高定量分析的精度,定标曲线拟合相关系数从传统定量分析方法的0.689提高到0.980;SVM定量分析方法训练集得到的定标曲线斜率近似为1,拟合相关系数为0.998,优于传统定量分析方法和多元线性回归分析方法,对检验集的预测相对误差均在2.57%以内。LIBS技术结合多元线性回归和SVM定量分析方法可以有效的提高土壤中Cr元素定量分析的稳定性和精度,校正土壤基体效应对Cr元素定量分析的影响。
[Abstract]:Laser induced breakdown spectroscopy (LIBS) combined with support vector machine (SVM) was used to determine the content of Cr in soil.The Nd:YAG pulse laser with wavelength of 1 064nm was used as the excitation light source. The LIBS characteristic spectra of soil samples with different heavy metal contents were detected by grating spectrometer and CCD spectrometer.The results show that the accuracy of quantitative analysis can be improved effectively by using multivariate linear regression analysis.The correlation coefficient of calibration curve fitting is improved from 0.689 of the traditional quantitative analysis method to 0.980 SVM quantitative analysis method. The slope of calibration curve is approximately 1, and the fitting correlation coefficient is 0.998, which is superior to the traditional quantitative analysis method and multivariate linear regression analysis method.The relative error of prediction of test set is within 2.57%. Libs combined with multiple linear regression and SVM quantitative analysis method can effectively improve the stability and accuracy of Cr quantitative analysis in soil.The effect of soil matrix effect on the quantitative analysis of Cr was corrected.
【作者单位】：中国科学院合肥物质科学研究院安徽光学精密机械研究所中国科学院环境光学与技术重点实验室;中国科学技术大学;
【基金】：国家(863计划)项目(2013AA065502,2014AA06A513) 安徽省杰出青年科学基金项目(1508085JGD02) 国家自然科学基金项目(61378041)资助
【分类号】：X833;O657.3

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