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Real time and high-precision online determination of main components in iron ore using spectral refinement algorithm based LIBS

光学 材料科学 规范化(社会学) 杂散光 激光器 光谱学 均方根 校准 紫外线 均方误差 近红外光谱 测距 激光诱导击穿光谱 算法 计算机科学 物理 数学 电信 统计 社会学 量子力学 人类学
作者
An Li,Xinyu Zhang,Xiaodong Liu,Yage He,Yuheng Shan,Haohan Sun,Yi Wen,Ruibin Liu
出处
期刊:Optics Express [Optica Publishing Group]
卷期号:31 (23): 38728-38728 被引量:5
标识
DOI:10.1364/oe.505574
摘要

The real-time online quantitative analysis instrument is highly desirable for many industrial fields. Herein, a new laser-induced breakdown spectroscopy (LIBS) setup with optimized optical route and high accuracy algorithm is designed and applied in a real industrial site. The components of total iron (TFe), silica (SiO2), aluminum oxide (Al2O3), and phosphorus (P) are quantitatively determined by the online LIBS system. The key optical part is a Maksutov-Cassegrain telescope, in which, two aspherical mirrors are specially designed and fabricated to reflect the broadband emission from ultraviolet 240 nm to infrared 890 nm with reflectivity over 90%, and pass the excited laser line of 1064 nm. The system could automatically adjust the focal length in the range of 780 mm to 940 mm. Based on the online LIBS system, the spectral pretreatment algorithm is also optimized including baseline removal and spectral normalization. The overlapped window slide (OWS) algorithm avoids the deformation of emission peaks in spectral baseline removal, in addition, two normalization steps by total back area and total spectral intensity within the sub-channel are applied to improve the spectral data stabilization. The calibration and validation are performed by utilizing the emissions that are insensitive to the detection distance. Compared with the traditional method, the prediction result shows that the root of mean square error of prediction (RMSEP) decreased from 5.091% to 1.2328%, and the mean absolute error (MAE) reduced from 4.801% to 0.9126% for TFe. Eventually, the online measurement shows good agreement with the official standard results. The high-precision online determination system based on LIBS will upgrade low frequency sampling of traditional detection to high-frequency real online determination in many industrial fields.
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