激光与光电子学进展, 2019, 56 (14): 143001, 网络出版: 2019-07-12 复制并引用该论文  被引通知

图 & 表

图 1. LIBS实验装置示意图

Fig. 1. Diagram of LIBS experimental setup

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图 2. 油漆涂层中的Pb元素在308~417 nm内的特征谱线

Fig. 2. Characteristic spectra of lead in paint coatings at 308-417 nm

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图 3. Pb I 405.78 nm分析线的定标曲线

Fig. 3. Calibration curve of 405.78 nm analytical line of Pb I

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图 4. 多元线性回归模型对校正集的预测结果

Fig. 4. Prediction results of multiple linear regression model for correction set

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图 5. CARS算法对波长变量的筛选结果。(a)波长变量数的变化趋势;(b) RMSECV的变化趋势;(c)各变量回归系数的变化趋势

Fig. 5. Screening results of wavelength variables by CARS algorithm. (a) Trend of variable number of wavelength; (b) trend of RMSECV; (c) trend of regression coefficients of various wavelength variables

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图 6. CARS算法筛选出的波长变量分布

Fig. 6. Distribution of wavelength variables screened by CARS algorithm

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图 7. CARS-PLS模型对校正集的预测结果

Fig. 7. Prediction results of CARS-PLS model for correction set

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表 1油漆涂层样品中Pb元素的参考含量

Table1. Reference content of lead in paint coating samples

Sample number Reference content /% 1# 0.014 2# 0.015 3# 0.027 4# 0.036 5# 0.042 6# 0.055 7# 0.11 8# 0.15 9# 0.17 10# 0.24

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表 2各分析模型对预测集样品的预测结果

Table2. Prediction result of each analysis model for sample of prediction set

Predictset Referencecontent /% Univariate calibration MLR ALL-PLS CARS-PLS Predictedcontend /% Relativeerror /% Predictedcontend /% Relativeerror /% Predictedcontend /% Relativeerror /% Predictedcontend /% Relativeerror /% 4# 0.036 0.032 11.1 0.0403 11.9 0.0317 11.9 0.0365 1.4 7# 0.11 0.093 15.5 0.1086 1.3 0.1199 9.0 0.1116 1.5

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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.