激光诱导击穿光谱单变量及多元线性回归方法研究
Research on Univariate and Multiple Linear Regression Calibration Methods by Laser Induced Breakdown Spectroscopy

余洋赵南京 ^* 王寅方丽孟德硕胡丽谷艳红王园园马明俊刘建国刘文清

文摘	为了提高激光诱导击穿光谱技术的检测能力和准确性,分别采用单变量分析和多变量分析方法[多元线性回归(MLR)]对样品中Cr进行定量分析。分别利用CrI:425.435 nm和CrI:427.48 nm两条特征谱线进行单变量分析,并在5种不同激光能量下获得了Cr的检测限,结果表明谱线CrI:425.435 nm的分析结果要优于CrI:427.48 nm,获得Cr最佳的检测限为5.8 mg/g。利用多变量分析方法,研究了浓度预测值与浓度实际值之间的线性相关性,与单变量分析方法相比,线性相关性由0.98提高到了0.99以上;采用留一交叉验证方法,比较了两种方法的预测相对误差(REP),单变量分析方法的REP分别为6.73%和7.59%,而MLR分析方法的REP则为4.66%,结果表明激光诱导击穿光谱技术结合MLR能够提高样品浓度预测的准确性。
其他语种文摘	In order to improve the detection capability and accuracy of laser-induced breakdown spectroscopy (LIBS), the univariate and multivariate method [multiple linear regression (MLR)] are adopted to make quantitative analysis on Cr contained in samples respectively. Univariate analysis has been made by use of two characteristic spectral lines CrI:425.435 nm and CrI:427.48 nm, the limits of detection are obtained under the condition of five laser energies. The results indicate that the analytical results of CrI:425.435 nm are better than CrI:427.48 nm, the best limit of detection of Cr is achieved 5.8 mg/g. The linear correlation between the prediction and actual values of concentration of samples is discussed using MLR, the correlation coefficient is increasing to above 0.99 from 0.98 compared with univariate method. Using the approach of leave-one-cross-validation, the relative errors of prediction (REP) of univariate analysis of CrI:425.435 nm and CrI:427.48 nm are 6.73% and 7.59% respectively, while the REP of MLR is reduced to 4.66%. The results indicate that LIBS combined with MLR can improve the accuracy of prediction on concentration of samples.
来源	激光与光电子学进展 ,2015,52(9):093001-1-093001-6 【核心库】
DOI	10.3788/LOP52.093001
关键词	光谱学 ; 激光诱导击穿光谱 ; 重金属 ; 铬 ; 单变量校正 ; 多元线性回归
地址	中国科学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, 安徽, 合肥, 230031
语种	中文
文献类型	研究性论文
ISSN	1006-4125
学科	物理学
基金	国家自然科学基金 ; 国家863计划 ; 安徽省杰出青年科学基金 ; 中国科学院仪器设备功能开发技术创新项目
文献收藏号	CSCD:5548623