自动寻峰是进行光谱原位探测、 实时自动分析的必要环节, 对拓展光谱分析技术到长期海洋监测、 石油录井等应用领域具有重要意义。 该研究以实验室中获得的LIBS/Raman光谱数据, 对Gaussian, Lorenz, Voigt三种线型函数构建的对称零面积变换函数进行了比较研究。 结果证明各个光谱峰都存在一个最优的对称零面积变换函数, 但三种变换函数在各自的最优化参数下获得的峰位、 峰宽一致; 以实验室中LIBS和Raman光谱定量实验数据对该方法的测试还证明, 对称零面积变换寻峰方法对信号的大范围动态变化适应性强, 弱峰识别能力达到或优于人工识别水平, 有望应用于将来的LIBS/Raman自动原位分析中去。

Automatic peak seeking is an indispensable link for in situ and real-time spectral detection and analysis, and has important significance for application of spectral technology to such fields as long-term marine monitoring and oil mud logging. Based on some typical LIBS/Raman spectrum data obtained from lab, three kinds of symmetric zero-area transformation functions respectively constructed from Gaussian, Lorentz and Voigt function were compared, and the results show that there exists an optimal symmetrical zero-area transformation function for peak seeking, but all the transformation functions obtain the same peak position and peak width under their optimal parameters. The proposed method is free from spectrum background and baseline trend influence, adaptive to the wide range of SNR, close to or even better than artificial recognition for weak peak, and could be used in future automatic in-situ analysis of LIBS and Raman.