Quantitative Analysis of Laser-Induced Breakdown Spectroscopy of Heavy Metals in Water Based on Biogeography-Based Optimization Algorithm

被引：2
|
作者：
Liu Lixin [1 ]
Sun Luogeng [1 ]
Li Mengzhu [1 ]
Zhu Ming [2 ]
机构：
[1] Xidian Univ, Sch Phys & Optoelect Engn, Xian 710071, Shaanxi, Peoples R China
[2] Shenzhen Univ, Coll Optoelect Engn, Shenzhen 518060, Guangdong, Peoples R China
来源：
LASER & OPTOELECTRONICS PROGRESS | 2018年 / 55卷 / 09期
关键词：
spectroscopy; laser-induced breakdown spectroscopy; biogeography-based optimization algorithm; water pollution; heavy metal;
D O I：
10.3788/LOP55.093005
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Laser-induced breakdown spectroscopy (LIBS) technology is an clement analysis technology based on atomic emission spectroscopy and plasma emission spectroscopy. In this study, LIES is used to detect the lead (Pb) concentrations in water. The strongest spectral line of Pb 105.8 mu is selected as the analytical line and Si 390.6 nm is used as internal standard clement. The detection limit of Pb obtained by linear fitting is determined to be 7.40X 10(-6) . A quantitative analysis model based on biogeography-based optimization (RHO) algorithm is established. Using this model, we establish the LIES spectra of 35 samples with different Pb concentrations. Among them, 30 sets of data are used to train the RHO 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 (MAPS) of the model are quite good when using the RHO algorithm model to predict the Pb concentration in water.
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页数：6
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