目的 为了探究一种基于光谱分析的检验方法，以达到快速准确地区分检验烟盒物证的目的。方法 采用便携式差分拉曼光谱仪，对39个不同的黄色烟盒样本进行测试，取得各样本的差分拉曼光谱数据。根据烟盒填料种类对样本进行初步分类，再结合化学计量学，通过IBM SPSS Statistics 26.0软件，在主成分分析法对数据进行降维的基础上，对测量结果进行系统聚类和K-Means聚类。结果 39种样本依据填料种类可以区分为3类，结合化学计量学可以更准确地区分为6类。结论 该方法无损检材、快捷准确，且图谱不受荧光干扰，结合化学计量学方法可以对烟盒样本进行分类检验，此方法为公安机关在犯罪现场检验此类物证提供了依据。

The work aims to explore a test method based on spectral analysis to achieve rapid and accurate identification of cigarette case evidence. Thirty-nine different yellow cigarette cases were tested with portable differential Raman spectrometer. The differential Raman spectra data of each sample were obtained. The samples were preliminary classified according to the type of filler. On the basis of data dimension reduction through principal component analysis, the results were clustered by Hierarchical clustering and K-Means clustering with IBM SPSS Statistics 26.0 software. The 39 samples could be divided into 3 categories according to the type of filler. And they could be further divided into 6 categories in combination with chemometrics. The results show that the method is non-destructive, fast and accurate, and the spectrum is not affected by fluorescence interference. Combined with chemometrics method, the cigarette case samples can be classified and tested. This method provides a basis for public security organs to test such material evidence at the scene of crime.