激光诱导击穿光谱(LIBS)中通常含有丰富的元素特征谱峰，谱峰的准确识别是利用LIBS技术进行元素定性、定量分析的前提和基础。针对传统谱峰元素识别方法准确率偏低、可靠性不足的缺点，提出了一种元素谱峰自动识别的新方法。该方法首先利用Voigt函数对实验光谱进行拟合，以克服谱峰重叠和噪声干扰; 通过滤波处理后提取拟合谱峰的中心波长、光强、半峰全宽和谱峰质心作为谱峰特征参数向量，并将待识别光谱的谱峰特征参数向量与美国国家标准与技术研究院(NIST)标准谱线数据库中的元素谱线进行相似性分析，从而实现谱峰元素的自动识别。分别利用NIST标准数据库和茶叶样品LIBS光谱数据进行实验研究，验证了该方法在LIBS谱峰元素识别上的有效性。

Laser-induced breakdown spectroscopy (LIBS) usually contains rich element characteristic spectrum peaks. The accurate identification of spectral peaks is the premise and basis for qualitative and quantitative elements analysis in LIBS technique. In this paper, a new method for automatic identification of spectral peaks is proposed to overcome the disadvantages of low accuracy and reliability of traditional spectral peak recognition methods. Firstly, the Voigt function is used to fit the experimental spectrum to overcome the overlapping spectrum and noise interference. Then, the center wavelength, light intensity, full width at half maximum and peak centroid of the fitting spectrum are extracted as the characteristic parameter vector of spectral peak after fitting process. Finally, the similarity analysis of the characteristic parameter vector of spectral peak between the spectrum to be recognized and the spectrum in National Institute of Standards and Technology (NIST) standard spectral database is carried out, so as to realize the automatic recognition of the spectral peak corresponding elements. Experiments are carried out using NIST standard database and LIBS spectra of tea samples, and the effectiveness of the method for spectral element recognition based on LIBS is verified.