激光与光电子学进展, 2019, 56 (14): 143001, 网络出版: 2019-07-12  

激光诱导击穿光谱结合CARS变量筛选检测油漆涂层中的Pb 下载: 951次

Pb Detection in Paint Coatings Through Combined Laser-Induced Breakdown Spectroscopy and CARS Variable Screening
作者单位
武汉理工大学理学院, 湖北 武汉 430070
摘要
利用激光诱导击穿光谱(LIBS)技术,对油漆涂层中的重金属Pb进行定量检测研究。优化实验参数后,利用多通道光谱仪采集油漆涂层308~417 nm范围内的等离子光谱,为了得到精确的定量结果,对油漆涂层的Pb分别进行单变量分析、多元线性回归分析以及竞争自适应再加权采样-偏最小二乘(CARS-PLS)分析。结果表明,CARS-PLS分析模型的定量结果最准确,校正集的决定系数为0.991,预测样品4#、7#的预测相对误差分别为1.4%、1.5%;CARS变量筛选方法能够从光谱中有效筛选出与Pb相关的重要信息,能够结合PLS准确检测油漆涂层中的Pb。
Abstract
Laser-induced breakdown spectroscopy (LIBS) was applied in this study to quantitatively detect heavy metal lead (Pb) in paint coatings. By optimizing experimental parameters, the plasma spectrum of the paint coating within 308-417 nm was collected using a multi-channel spectrometer. Univariate and multivariate linear regression together with competitive adaptive reweighted sampling-partial least squares (CARS-PLS) analyses were later performed on the obtained Pb data of paint coatings to achieve more accurate quantitative results. Among the three analytical models, CARS-PLS displayed the highest accuracy; the determination coefficient of the calibration set was 0.991, and the relative errors of 4# and 7# of the predicted samples were 1.4% and 1.5%, respectively. Thus, CARS variable screening effectively screened important Pb-related data, and accurately detected Pb in the paint coating when combined with PLS.

吴子俊, 卢景琦, 黄剑, 程德伟. 激光诱导击穿光谱结合CARS变量筛选检测油漆涂层中的Pb[J]. 激光与光电子学进展, 2019, 56(14): 143001. Zijun Wu, Jingqi Lu, Jian Huang, Dewei Cheng. Pb Detection in Paint Coatings Through Combined Laser-Induced Breakdown Spectroscopy and CARS Variable Screening[J]. Laser & Optoelectronics Progress, 2019, 56(14): 143001.

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