激光与光电子学进展, 2018, 55 (9): 093005, 网络出版: 2018-09-08   

基于生物地理学优化算法的水体重金属激光诱导击穿光谱定量分析 下载: 607次

Quantitative Analysis of Laser-Induced Breakdown Spectroscopy of Heavy Metals in Water Based on Biogeography-Based Optimization Algorithm
作者单位
1 西安电子科技大学物理与光电工程学院, 陕西 西安 710071
2 深圳大学光电工程学院, 广东 深圳 518060
摘要
激光诱导击穿光谱(LIBS)技术是一种基于原子发射光谱和等离子体发射光谱的物质成分分析技术。利用LIBS技术对水中的Pb污染进行检测, 选择Pb元素的最强峰405.8 nm作为分析线, 以Si(390.6 nm)为内标元素, 经线性拟合得到Pb的检出限为7.40×10-6。建立了基于生物地理学优化(BBO)算法的定量分析模型, 利用该模型分别测定了不同Pb元素浓度的35份样品的LIBS谱线, 其中的30组数据被用来训练BBO定量分析模型, 剩余的5组数据被作为测试集来评估模型的分析能力。结果表明:在利用BBO算法模型对水体中Pb浓度进行预测时, 模型的相对标准偏差(RSD)及平均绝对百分比误差(MAPE)指标都相当优异。
Abstract
Laser-induced breakdown spectroscopy (LIBS) technology is an element analysis technology based on atomic emission spectroscopy and plasma emission spectroscopy. In this study, LIBS is used to detect the lead (Pb) concentrations in water. The strongest spectral line of Pb 405.8 nm is selected as the analytical line and Si 390.6 nm is used as internal standard element. The detection limit of Pb obtained by linear fitting is determined to be 7.40×10-6 . A quantitative analysis model based on biogeography-based optimization (BBO) algorithm is established. Using this model, we establish the LIBS spectra of 35 samples with different Pb concentrations. Among them, 30 sets of data are used to train the BBO quantitative analysis model, and the remaining 5 sets of data are used as test sets to evaluate the analytical ability of the model. The results show that the relative standard deviation (RSD) and the mean absolute percentage error (MAPE) of the model are quite good when using the BBO algorithm model to predict the Pb concentration in water.

刘立新, 孙罗庚, 李梦珠, 祝铭. 基于生物地理学优化算法的水体重金属激光诱导击穿光谱定量分析[J]. 激光与光电子学进展, 2018, 55(9): 093005. Liu Lixin, Sun Luogeng, Li Mengzhu, Zhu Ming. Quantitative Analysis of Laser-Induced Breakdown Spectroscopy of Heavy Metals in Water Based on Biogeography-Based Optimization Algorithm[J]. Laser & Optoelectronics Progress, 2018, 55(9): 093005.

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