目的 对纵火类案件现场所遗留食用油油桶物证进行快速无损检验及区分，为公安机关侦查破案提供线索。方法 采用最新的差分拉曼光谱技术对26个食用油油桶及桶盖，共计52个样品进行检验。首先，通过传统谱图分析对2类样品进行初步分类，同时，结合多元分析，对桶盖进行分层聚类，对桶身再利用Gap statistic算法确定k值的基础上K-means聚类分析。结果 成功将桶盖分为了3类，桶身分为3类，且对桶盖和桶身所得分类结果都与已知样品所属类别一致。结论 此方法可对食用油油桶进行快速无损检验及区分，为现场遗留有食用油油桶的纵火案件侦破提供一定的帮助。

The work aims to conduct rapid non-destructive inspection and differentiation of the physical evidence of edible oil barrels left on the scene of arson cases, and provide clues for the public security organs to investigate and solve the case. A total of 52 samples of 26 pairs of edible oil barrels and bungs were tested by the latest differential Raman spectroscopy technology. Firstly, the two types of samples were preliminarily classified through traditional spectral analysis. At the same time, combined with multivariate analysis, hierarchical clustering was performed to the bungs and K-means cluster analysis was carried out to the barrels based on the Gap statistic algorithm to determine the k value. The bungs and barrels were successfully divided into 3 categories, respectively. The classification results were consistent with the category of the known samples. Through this method, the rapid non-destructive inspection and differentiation of edible oil barrels can be performed, which provides certain help for the detection of arson cases where edible oil barrels are left on the scene.