针对工业现场和野外恶劣环境下快速检测的需求, 设计并搭建了基于光纤激光器的便携式激光诱导击穿光谱实验系统.采用迭代小波变换去背景算法对光纤激光器的高重复频率造成的高的连续背景干扰进行消除.对比了去背景前后攀钢生铁样品中的Mn元素的谱线, 发现Mn元素的4条特征谱线的定标曲线决定系数分别由0.988、0.985、0.982和0.992提高到了0.994、0.994、0.994和0.995; 采用留一交叉验证得到的均方根误差分别从0.123、0.146、0.101和0.083, 降低到了0.072、0.085、0.062和0.073.结果表明, 采用该迭代的小波变换去背景算法, 能够有效地去除连续背景干扰, 提高回归模型的准确性, 进而提高激光诱导击穿光谱定量分析的准确度.

A portable laser-induced breakdown spectroscopy system based on fiber laser was developed to meet the demand of rapid detection in industrial field and rugged environment. A algorithm of background removal based on iterative wavelet transform was used to eliminate the high continuous background interference caused by the high repetition rate of the fiber laser. The emission lines of element Mn in pig iron samples were compared before and after the background removal. After background removal by the iterative wavelet transform algorithm, the determination coefficient of calibration curve for four emission lines of element Mn was improved from 0.988, 0.985, 0.982 and 0.992, to 0.994, 0.994, 0.994 and 0.995, respectively, and the root-mean-square error of cross-validation was decrease from 0.123, 0.146, 0.101 and 0.083, to 0.072, 0.085, 0.062 and 0.073, respectively. The results show that the algorithm of iterative wavelet transform can effectively remove the continuous background interference, improve the accuracy of regression model, and then improve the accuracy of quantitative analysis.