为了将太赫兹光谱分析技术应用于物质识别领域，需要建立太赫兹波段的光谱数据库，并研究合适的数据库使用方法，以鉴别未知物质。光谱获取采用自行搭建的太赫兹时域光谱测量系统，通过小波变换去除基线和噪声等干扰信息，建立起含有20种典型有机物的光谱数据库。使用该数据库识别未知物质时，分成两步：1) 用径向基函数神经网络算法判断未知物质是否在数据库中；2) 若在数据库中，采用基于纠错输出编码的支持向量机多类算法鉴别物质种类。测试结果表明，对库内物质识别率为96.7%，对库外物质也有较好的预测和推断能力，识别率为93.2%。提出的太赫兹光谱数据库建立和使用方法，对系统噪声等干扰因素有很好的抑制作用，可以应用到实际场合。

Terahertz spectroscopy provides a new way for material identification. Investigation on establishment and usage methods of terahertz spectral database is needed so as to distinguish unknown substances. In order to establish the database, terahertz spectra of twenty organic materials are measured by own built terahertz time-domain spectroscopy system and the interference information of baseline and noise are removed by wavelet transform. The usage of database is divided into two steps: 1) determine whether the unknown substance is in the database through the radial basis function neural network; 2) identify the material if it is in the database by multi-class support vector machine. The fault tolerance of the algorithm is improved combined with error-correcting output coding to handle the multi-class problem with recognition rate of 96.7%. The network also has a good prediction of materials outside database with recognition rate of 93.2%. The establishment and usage methods of the database suppress the system noise and can be applied to practical situations.