光学学报, 2015, 35 (6): 0630001, 网络出版: 2015-06-02   

基于多元校正的水体Pb元素LIBS定量分析

Quantitative Analysis of Pb in Water Based on Multivariate Calibration with LIBS
作者单位
中国科学院安徽光学精密机械研究所环境光学与技术重点实验室, 安徽省环境光学与技术重点实验室, 安徽 合肥 230031
摘要
在水体重金属激光诱导击穿光谱(LIBS)检测中,湖库水体组分的复杂性以及不同水域水质的差异加剧了基体效应对定量分析精密度和准确度的影响。为减小系统参数波动以及基体效应的影响,针对湖库水体不同采样点的水样,通过背景、内标元素校正待测元素的特征谱线,研究峰值强度、积分强度、信背比和内标校正强度组成的不同输入向量对支持向量机回归模型的影响,结果表明信背比和内标校正强度组成的二元输入向量回归效果最好,训练集均方根误差和相关系数分别为0.367 和0.981,测试集的相对标准偏差和相对误差平均值分别为4.5%和12.1%。经过校正的多元输入向量,可以有效减小参数波动和基体差异的影响,为自然水体重金属LIBS定量分析提供数据输入方面的参考。
Abstract
Complex components of lakes and water difference between different sampling points contribute to the matrix effect influence on precision and accuracy of quantitative analysis with laser induced breakdown spectroscopy (LIBS). To reduce the fluctuation of system parameters and the matrix effect caused by the sample enrichment and water quality difference, characteristic spectral lines of the element under test are corrected with the background and the internal standard element. The influence of different input vectors on support vector regression (SVR) model is studied, including the peak intensity, integral intensity and signal to background ratio. Comparison results show that the effect of SVR model with binary input vector of signal to background ratio and intensity corrected by internal standard element is the best, and the root mean square error and the correlation coefficient of training set are 0.367 and 0.981, respectively, and the relative standard deviation and the average relative error of test set are 4.5% and 12.1% respectively. Multiple input vector carrying more characteristic spectral lines can effectively reduce the influence of parameter fluctuations and substrate difference. The experimental conclusion provides reference for data input in LIBS quantitative analysis of heavy metals in natural water.

胡丽, 赵南京, 刘文清, 方丽, 王寅, 孟德硕, 余洋, 谷艳红, 王园园, 马明俊, 肖雪, 王煜, 刘建国. 基于多元校正的水体Pb元素LIBS定量分析[J]. 光学学报, 2015, 35(6): 0630001. Hu Li, Zhao Nanjing, Liu Wenqing, Fang Li, Wang Yin, Meng Deshuo, Yu Yang, Gu Yanhong, Wang Yuanyuan, Ma Mingjun, Xiao Xue, Wang Yu, Liu Jianguo. Quantitative Analysis of Pb in Water Based on Multivariate Calibration with LIBS[J]. Acta Optica Sinica, 2015, 35(6): 0630001.

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