光谱学与光谱分析, 2014, 34 (8): 2244, 网络出版: 2014-08-18   

基于LIBS技术的钢铁合金中元素多变量定量分析方法研究

Study on the Multivariate Quantitative Analysis Method for Steel Alloy Elements Using LIBS
作者单位
中国海洋大学光学光电子实验室, 山东 青岛266100
摘要
针对钢铁合金样品元素组成相对复杂, 基体效应较严重的问题, 利用激光诱导击穿(LIBS)光谱技术对钢铁合金中的元素进行了定量分析。以Nd∶YAG脉冲激光器基频1 064 nm波长激光作为激发光源, 采用中阶梯光栅光谱仪和ICCD分光探测钢铁合金样品的LIBS光谱。通过优化实验确定最佳探测延时为1.5 μs, 最佳探测门宽为2 μs, 激光聚焦点位置在实验样品靶面以下1.5 mm。采用单变量定量分析、 多变量线性回归和偏最小二乘(PLS)三种方法分析钢铁合金中Cr元素和Ni元素的含量。结果表明, 采用单变量定标方法定标曲线相关系数不高, 对待测样的预测误差相对较大, 难以有效地定量分析基体元素复杂的钢铁合金中金属元素的含量; 采用多变量线性回归分析方法能有效提高定量分析的精度; 采用PLS方法得到的Cr和Ni元素的拟合曲线相关系数r分别为0.981和0.995, 对两个待测样品中Cr元素和Ni元素的预测相对误差在6.4%和7.1%以内, 分析结果优于多变量线性回归方法。可见, 采用多变量校正的PLS方法能更有效地校正基体效应对定量分析的影响, 提高定量分析的精度。
Abstract
Quantitative analysis of steel alloys was carried out using laser induced breakdown spectroscopy ( LIBS ) taking into account the complex matrix effects in steel alloy samples. The laser induced plasma was generated by a Q-switched Nd∶YAG laser operating at 1 064 nm with pulse width of 10 ns and repeated frequency of 10 Hz. The LIBS signal was coupled to the echelle spectrometer and recorded by a high sensitive ICCD detector. To get the best experimental conditions, some parameters, such as the detection delay, the CCD's integral gate width and the detecting position from the sample surface, were optimized. The experimental results showed that the optimum detection delay time was 1.5μs, the optimal CCD's integral gate width was 2 μs and the best detecting position was 1.5 mm below the alloy sample’s surface. The samples used in the experiments are ten standard steel alloy samples and two unknown steel alloy samples. The quantitative analysis was investigated with the optimum experimental parameters. Elements Cr and Ni in steel alloy samples were taken as the detection targets. The analysis was carried out with the methods based on conditional univariate quantitative analysis, multiple linear regression and partial least squares (PLS) respectively. It turned out that the correlation coefficients of calibration curves are not very high in the conditional univariate calibration method. The analysis results were obtained with the unsatisfied relative errors for the two predicted samples. So the conditional univariate quantitative analysis method can't effectively serve the quantitative analysis purpose for multi-components and complex matrix steel alloy samples. And with multiple linear regression method, the analysis accuracy was improved effectively. The method based on partial least squares (PLS) turned out to be the best method among all the three quantitative analysis methods applied. Based on PLS, the correlation coefficient of calibration curve for Cr is 0.981 and that for Ni is 0.995. The concentrations of Cr and Ni in two target samples were determined using PLS calibration method, and the relative errors for the two unknown steel alloy samples are lower than 6.62% and 1.49% respectively. The obtained results showed that in the quantitative analysis of steel alloys, the matrix effect would be reduced effectively and the quantitative analysis accuracy would be improved by the PLS calibration method.

谷艳红, 李颖, 田野, 卢渊. 基于LIBS技术的钢铁合金中元素多变量定量分析方法研究[J]. 光谱学与光谱分析, 2014, 34(8): 2244. GU Yan-hong, LI Ying, TIAN Ye, LU Yuan. Study on the Multivariate Quantitative Analysis Method for Steel Alloy Elements Using LIBS[J]. Spectroscopy and Spectral Analysis, 2014, 34(8): 2244.

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