文章摘要
姜红,田陆川,王艺霖,段斌,刘峰.差分拉曼光谱法结合聚类分析检验食品塑料包装盒[J].包装工程,2021,42(15):85-93.
JIANG Hong,TIAN Lu-chuan,WANG Yi-lin,DUAN Bin,LIU Feng.Differential Raman Spectroscopy Combined with Cluster Analysis for Inspection of Food Plastic Packaging Box[J].Packaging Engineering,2021,42(15):85-93.
差分拉曼光谱法结合聚类分析检验食品塑料包装盒
Differential Raman Spectroscopy Combined with Cluster Analysis for Inspection of Food Plastic Packaging Box
投稿时间:2021-01-12  
DOI:10.19554/j.cnki.1001-3563.2021.15.010
中文关键词: 差分拉曼  光谱技术  聚类分析  食品塑料包装盒
英文关键词: differential raman  spectroscopy  cluster analysis  food plastic packaging box
基金项目:中国人民公安大学基科费重点项目(2019JKF222)
作者单位
姜红 中国人民公安大学 侦查学院北京 100038 
田陆川 中国人民公安大学 侦查学院北京 100038 
王艺霖 中国人民公安大学 侦查学院北京 100038 
段斌 南京简智仪器设备有限公司南京 210049 
刘峰 南京简智仪器设备有限公司南京 210049 
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中文摘要:
      目的 建立一种高效、无损、准确的区分检验食品塑料包装盒的方法。方法 采用SERDS Portable-Standard便携式差分拉曼光谱仪,在激发光源为785 nm,激光功率为380 mW,扫描时间为10 s,扫描范围为250~2800 cm1的实验条件下,对53个不同来源、不同品牌的食品塑料包装盒样品进行测量,对得到的差分拉曼光谱数据进行凝聚性系统聚类分析,并结合皮尔逊相关性系数对其进行检验,对食品塑料包装样品进行区分。结果 53个样品根据差分拉曼谱图被分为7类,根据不同样品的差分拉曼特征峰聚类结果将32个PP类样品分为4类。结论 该方法无损检测、操作便捷、实验结果稳定,可以为微量物证检验和侦查破案提供一定帮助。
英文摘要:
      The work aims to establish an efficient, nondestructive and accurate method for distinguishing and testing food plastic packaging boxes. SERDs Portable-Standard was used to measure 53 samples of food plastic packaging boxes from different sources and brands under the experimental conditions of 785 nm excitation source, 380 mW laser power, 10 s scanning time and 250-2800 cm−1 scanning range.The obtained differential Raman spectrometer data were analyzed by cohesive systematic clustering and examined in combination with Pearson correlation coefficient to distinguish the plastic packaging samples of food. The 53 samples were divided into 7 groups according to the differential Raman spectra, and 32 PP samples were divided into 4 groups according to the clustering results of different samples. The method is non-destructive, easy to operate, and the experimental results are stable, which can provide some help for the detection of trace evidence and the detection of cases.
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