激光与光电子学进展, 2016, 53 (5): 053002, 网络出版: 2016-05-05
基于改进多元非线性模型的LIBS钢液成分定量分析
Quantitative Analysis of Liquid Steel Component by LIBS Based on Improved Multivariate Nonlinear Model
光谱学 激光诱导击穿光谱 多元二次非线性函数 钢液定量分析 spectroscopy laser-induced breakdown spectroscopy multivariate quadratic nonlinear function liquid steel quantitative analysis
摘要
激光诱导击穿光谱(LIBS)技术用于钢液成分在线定量分析时, 基体效应会对其精确度产生严重影响。在定量分析时,用一种改进的多元非线性模型进行定标,以降低基体效应对待测元素的影响,并与单变量定标和改进前的多元非线性模型定标进行对比。结果表明,与单变量定标相比,多元非线性模型定标的测量精度有所提高,模型改进后,其分析性能得到进一步完善。测量元素Mn、Si的定标曲线的拟合度从0.980、0.984分别提高到0.985、0.989,两个验证样品的预测相对误差分别从6.231%、5.437%和6.912%、6.315%下降到5.510%、5.039%和6.125%、5.919%。
Abstract
When the laser-induced breakdown spectroscopy (LIBS) is used for on-line quantitative analysis of liquid steel, matrix effect shows serious impact on the analysis accuracy. In the quantitative analysis, an improved multivariate nonlinear calibration method is used to reduce the matrix effect. The improved method is compared with univariate calibration and unimproved multivariate nonlinear calibration. The results show that the multivariate nonlinear calibration exhibits better accuracy compared with the univariate calibration method. The analytical performance is improved further after the multivariate model is improved. The fitting degree of calibration curves for measurement of Mn, Si elements increases from 0.980, 0.984 to 0.985, 0.989, respectively. The relative error for prediction of two validation samples decreases from 6.231%, 5.437% and 6.912%, 6.315% to 5.510%, 5.039% and 6.125%, 5.919%, respectively.
杨友良, 王鹏, 马翠红. 基于改进多元非线性模型的LIBS钢液成分定量分析[J]. 激光与光电子学进展, 2016, 53(5): 053002. Yang Youliang, Wang Peng, Ma Cuihong. Quantitative Analysis of Liquid Steel Component by LIBS Based on Improved Multivariate Nonlinear Model[J]. Laser & Optoelectronics Progress, 2016, 53(5): 053002.