Sun Lan-Xiang, Yu Hai-Bin, Xin Yong, Cong Zhi-Bo
Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2010 Dec;30(12):3186-90.
The concentration of Mn and Si in different kinds of steels was determined by laser-induced breakdown spectroscopy (LIBS). The multivariate quadratic nonlinear function was adopted for calibration. Samples including common alloy steels, stainless steels and carbon tool steels were analyzed. The matrix effect was serious because of large difference in compositions of different kinds of steels and strong line overlaps in steel spectra. Therefore, the common calibration methods that only use one analytical line to calibrate the complex chemical compositions of alloy steels will lose much information. The multivariate calibration methods, however, can utilize more information of spectra, successfully reduce the matrix effect and improve the measurement repeatability and accuracy of LIBS. Compared with the common calibration method based on one analytical line, the relative standard deviation was reduced from above 20% to below 10%, and the accuracy was increased by more than 5 times for Mn and more than 6 times for Si.
采用激光诱导击穿光谱法（LIBS）测定了不同种类钢中锰和硅的含量。采用多元二次非线性函数进行校准。分析了包括普通合金钢、不锈钢和碳素工具钢在内的样品。由于不同种类钢的成分差异较大且钢光谱中谱线重叠严重，基体效应较为严重。因此，仅使用一条分析线来校准合金钢复杂化学成分的常规校准方法会丢失大量信息。然而，多元校准方法可以利用光谱的更多信息，成功降低基体效应，提高LIBS测量的重复性和准确性。与基于一条分析线的常规校准方法相比，相对标准偏差从20%以上降至10%以下，锰的准确度提高了5倍以上，硅的准确度提高了6倍以上。
