偏最小二乘回归
激光诱导击穿光谱
校准
分析化学(期刊)
均方误差
基质(化学分析)
光谱学
材料科学
矿物学
化学
数学
环境化学
统计
复合材料
物理
量子力学
作者
Zhongqi Hao,Changqing Li,Mouquan Shen,Xin Yang,Kun Li,Lianbo Guo,Xiangyou Li,Yongfeng Lu,Xiaoyan Zeng
出处
期刊:Optics Express
[Optica Publishing Group]
日期:2015-03-17
卷期号:23 (6): 7795-7795
被引量:44
摘要
Laser-induced breakdown spectroscopy (LIBS) with partial least squares regression (PLSR) has been applied to measuring the acidity of iron ore, which can be defined by the concentrations of oxides: CaO, MgO, Al₂O₃, and SiO₂. With the conventional internal standard calibration, it is difficult to establish the calibration curves of CaO, MgO, Al₂O₃, and SiO₂ in iron ore due to the serious matrix effects. PLSR is effective to address this problem due to its excellent performance in compensating the matrix effects. In this work, fifty samples were used to construct the PLSR calibration models for the above-mentioned oxides. These calibration models were validated by the 10-fold cross-validation method with the minimum root-mean-square errors (RMSE). Another ten samples were used as a test set. The acidities were calculated according to the estimated concentrations of CaO, MgO, Al₂O₃, and SiO₂ using the PLSR models. The average relative error (ARE) and RMSE of the acidity achieved 3.65% and 0.0048, respectively, for the test samples.
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