激光与光电子学进展, 2019, 56 (22): 223003, 网络出版: 2019-11-02
多元校正输入的钢液Mn元素LIBS定量分析 下载: 829次
Quantitative Analysis of Mn in Molten Steel with Multi-Factor Calibration Input Using Laser-Induced Breakdown Spectroscopy
光谱学 激光诱导击穿光谱 定量分析 精准度 输入向量 spectroscopy laser-induced breakdown spectroscopy quantitative analysis presicion input vector
摘要
为了提高光诱导击穿光谱(LIBS)技术定量分析的精准度,用LIBS技术对不同合金钢中的Mn元素进行定量分析,结合支持向量回归(SVR)建立定标模型,研究输入向量对SVR模型的影响,并与校正后的内标法进行比较。结果表明:输入向量为内标元素校正和信背比时,测试集的相对标准偏差和相对误差的平均值分别为2.6%和11.97%,回归效果最理想;对合金钢中的Mn元素进行定量分析时,校正后的二元输入向量可以减小参数波动和校正基体效应的影响,为LIBS钢液元素定量分析优化数据输入提供了参考。
Abstract
To improve the accuracy of quantitative analysis of laser-induced breakdown spectroscopy (LIBS), the quantitative analysis of Mn in different alloy steels is conducted by LIBS. The calibration model is established by combining support vector regression (SVR) to study the influences of different input vectors in the SVR model, and the internal standard method is used to correct the results. The results show that when the input vectors are the internal standard element correction and signal-to-back ratio, the relative standard deviation and the relative error of the test set are 2.6% and 11.97%, respectively, and the regression effect is optimal. In the quantitative analysis of Mn in the alloy steel, the corrected binary input vector reduces the parameter fluctuation, corrects the matrix effect, and provides a reference for the optimization of the input data for the quantitative analysis of steel elements by LIBS.
杨友良, 王禄, 马翠红. 多元校正输入的钢液Mn元素LIBS定量分析[J]. 激光与光电子学进展, 2019, 56(22): 223003. Youliang Yang, Lu Wang, Cuihong Ma. Quantitative Analysis of Mn in Molten Steel with Multi-Factor Calibration Input Using Laser-Induced Breakdown Spectroscopy[J]. Laser & Optoelectronics Progress, 2019, 56(22): 223003.