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。
Laser-induced breakdown spectroscopy (LIBS) was used to calibrate the concentration of Cr in soils combined with Support Vector Machine. The Nd: YAG pulse laser with the wavelength of 1 064 nm was used as the excitation source. The grating spectrometer and the charge couple device were used as spectral separation device and the spectral detection device. The multiple linear regression and support vector machine were adopted to make quantitative analysis on Cr in soils respectively. The result indicate that the multiple linear regression can get more accurate informination of the spectral lines: the correlation coefficient is increased from 0. 689 to 0. 980 compared with conventional quantitative method. Thereofre, the the accuracy of quantitative analysis is increased. The slope about calibration curve with support vector machine of test set is nearly about 1 and the correlation coefficient is 0. 998, the relative errors for the test set all are lower than 2. 57%, the quantitative analysis results about support vector machine are better than the results combined with the conventional quantitative method and the multiple linear regression. The support vector machine can correct the matrix effect and improve the accuracy of prediction on the concentration of Cr in soil.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2016年第6期1893-1898,共6页
Spectroscopy and Spectral Analysis
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
关键词
激光诱导击穿光谱
土壤
CR元素
支持向量机
Laser-induced breakdown spectroscopy
Soil
Chromium
Support vector machine