目的 建立一种便捷精准无损检验眼药水塑料瓶的方法。方法 使用便携式差分拉曼光谱仪检测33个塑料眼药水瓶，根据获得的各样品数据，包括差分拉曼光谱图的峰位、峰数等对样品进行成分分析，并通过统计分析软件“统计产品与服务解决方案”(SPSS 26.0)对样品进行K均值聚类，利用轮廓系数优选K值。对分类结果中样品数目较多的一类样品进行填料分析，利用皮尔逊相关系数验证分析结果的准确性。结果 样品主要成分为聚乙烯和聚对苯二甲酸乙二醇酯，利用轮廓系数优选K值为2，K均值聚类算法对样品的分类结果与成分分析结果能够相互印证。以聚乙烯类样品为例，根据填料不同可将其分为7组。皮尔逊相关系数计算结果能够证明上述分类分组结果可靠。结论 利用该方法能够准确无损地检测眼药水塑料瓶，并对其进行分类研究。

The work aims to establish a rapid, accurate and nondestructive method for testing the plastic bottles of eye drops. Portable differential Raman spectrometer was used to test 33 plastic bottles of eye drops. Then, according to the sample data obtained such as peak position and peak number of the differential Raman spectrum, the composition of the samples was analyzed. At the same time, K-means clustering was carried out to the samples by statistical analysis software "Statistical Products and Services Solutions he most optimal K-means was selected based on Silhouette Coefficient. The samples with a large number in the classification results were analyzed, and the accuracy of the analysis results was verified by Pearson correlation coefficient. The samples were mainly composed of polyethylene and polyethylene terephthalate. The most optimal K-means selected based on Silhouette Coefficient was 2 and the K-means clustering algorithm verified the classification result and composition analysis result of the samples. With polyethylene samples as an example, they could be divided into 7 groups according to different fillers. The calculation results of Pearson correlation coefficient proved the reliability of the above classification and grouping results. This method can accurately and non-destructively detect and classify the plastic bottles of eye drops.