摘要
为建立一种利用拉曼光谱快速无损检验白色纸质购物袋的方法,利用便携式拉曼光谱仪,在激发波长为1064 nm、激发功率为500 mW、积分时间为5 s的条件下,对收集到的60个不同品牌、不同规格的白色购物纸袋样品进行光谱测定。依据样品中填料成分的不同,将样品分为三大类,以结合系统聚类分析方法和Pearson相关系数对第一类样品进行分析,将其分为四组,采用RBF神经网络模型对该类样品的分组结果进行验证,准确率可达100%。该方法简便易行,可为纸质样品的分类提供科学的依据,为公安机关实际办案提供技术支持。
To establish a method for rapid non-destructive testing of white paper shopping bags using Raman spectroscopy.A portable Raman spectrometer was used to determine the spectra of 60 white shopping paper bag samples of different brands and specifications collected under the conditions of excitation wavelength of 1064 nm,excitation power of 500 mW,and integration time of 5s.The results can be divided into three categories based on the different filler components in the samples.By combining the system clustering analysis method and Pearson correlation coefficient,the first type of samples can be analyzed and divided into four groups.The RBF neural network model is used to verify the grouping results of these samples,with an accuracy of up to 100%.This method is simple and feasible,and can provide scientific basis for the classification of paper samples,as well as technical support for the actual handling of cases by public security organs.
作者
谢佳宁
胡晓光
姜红
刘颖
Xie Jianing;Hu Xiaoguang;Jiang Hong;Liu Ying(People's Public Security University of China,Beijing 100038,China;Criminal Investigation Department,Gansu Police Vocational College,Gansu Lanzhou,730046;Beijing Jianzhi Technology Co.,Ltd,Beijing)
出处
《实验与分析》
2023年第2期41-46,共6页
LABOR PRAXIS
基金
中国人民公安大学刑事科学技术双一流创新研究专项(2023SYL06)。
关键词
白色纸质购物袋
拉曼光谱
填料
化学计量学
系统聚类
White paper shopping bag
Raman spectroscopy
Filler
Chemometrics
System clustering
