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红外光谱法结合化学计量学对可擦笔油墨检验的研究
作者单位:中国人民公安大学,刑事科学技术国家级实验教学中心,侦查学院,北京 100038;上海市公安局长宁分局,上海 200336
基金项目:公安部技术研究计划项目(2019JSYJC21),中央高校基本科研业务费专项资金项目(2019JKF214)资助
摘    要:可擦笔作为一种新型书写工具,具有墨迹可擦除的特点,因此在当前的公安司法工作中,常见不法分子利用可擦笔对文件进行篡改。为保证物证的完整性,亟待建立一种无损,快速的可擦笔油墨检验方法,为寻找书写工具,确定犯罪嫌疑人提供帮助。常见可擦笔油墨可分为成膜油墨类和温变油墨类,本研究利用傅里叶变换红外光谱仪对市场收集的不同品牌、型号和颜色的30支可擦笔油墨进行检验。通过分析4 000~650 cm-1范围内的红外光谱对比不同可擦笔油墨的组成成分及不同褪色机理的可擦笔油墨差异。通过红外光谱信息发现,同品牌、同型号的可擦笔油墨成分相似,可擦笔油墨颜色对红外光谱影响较小。同时,对比擦除前后的可擦笔墨痕的红外光谱信息发现,温变类油墨在擦除后依旧有特殊化学成分残留,具备检验条件,但成膜型可擦油墨在擦除后残留成分较少,很难进行认定,这可能与成膜类油墨的微粒结构有关。此外,本研究利用主成分分析法(PCA)和热图Heatmap对可擦笔油墨650~1 500 cm-1范围内的红外光谱信息进行处理,进而对可擦笔种类进行分类研究,并建立红外光谱信息与主成分载荷(loadings)之间的联系。通过载荷图可知,前两主成分概括了几乎全部的红外光谱信息,累计贡献率在79%以上。为在实际工作中判断可擦笔来源,在30种油墨样本中随机选取5种未知可擦笔样本,与已知样本同时进行PCA分析,并制作散点图,实现对未知可擦笔油墨样品种类的判断,效果较好。实验结果表明,利用傅里叶变换红外光谱结合主成分分析法可对可擦笔油墨较好地进行分类,具有快速、无损、高灵敏度的显著优势,在保证物证的完整性的同时,提高了检验效率,为可擦笔变造文件的检验提供了一种较为理想的分析方法。

关 键 词:傅里叶变换红外光谱  油墨  文件检验  可擦笔  主成分分析法  热图
收稿时间:2020-08-20

Identification of Different Brands Erasable Pens by Infrared Spectroscopy Combined With Chemometrics Methods
Authors:ZHAO Yu-xuan  ZENG Le-yang-zi  LI Kai-kai
Institution:1. College of Criminal Investigation, National Experimental Teaching Demonstrating Center, People’s Public Security University of China, Beijing 100038,China 2. Changning Branch of Shanghai Public Security Bureau, Shanghai 200336, China
Abstract:As a new writing tool, an erasable pen has the characteristics of erasable ink. Therefore, in the current public security work, common criminals use an erasable pen to tamper with documents. In order to ensure the integrity of material evidence, it is urgent to establish a non-destructive and rapid ink test of the erasable pen to provide help for finding writing tools and identifying criminal suspects. Common erasable pen inks can be divided into film-forming ink and temperature change ink. In this study, the ink of 30 erasable pens of different brands, types and colors were analyzed with Fourier transform infrared spectroscopy (FTIR). Through the analysis of infrared spectra in the range of 4 000~650 cm-1, the difference in their composition and the spectral difference of erasable pen with different fading mechanism were compared. Through the infrared spectrum information, it is found that the components of the same brand and the same model of erasable pen ink are similar, and the ink color has little influence on the infrared spectra. At the same time, comparing the infrared spectrum information of the erasable pen ink before and after erasing, it is found that there are still some special chemical components in the temperature change ink after erasing, which can be used as the identification standard. However, the residual components of film-forming ink are less after erasing, which is difficult to identify, which may be related to the particle structure of film-forming ink. In addition, the spectra in the range 650~1 500 cm-1 of erasable pen ink were analyzed by principal component analysis (PCA) and Heatmap to classify the types of erasable pen. The relationship between infrared spectrum information and principal component loadings was established. According to the loading plot, the first two principal components summarize almost all the infrared spectrum information, and the cumulative contribution rate is more than 79%. Therefore, the first two principal components are selected to a scatter plot. In order to determine the source of the erasable pen in practical work, 5 samples of the unknown pen were randomly selected from 30 kinds of ink samples, and PCA analysis was carried out with known samples at the same time, and a scatter diagram was made to realize the prediction of the types of unknown erasable pen ink samples and work well. The results indicate that FTIR combined with PCA can be used to classify the erasable pen ink rapidly. It provides a method for examining the erasable pen ink in altered documents with advantages of fast, non-destructive and high sensitivity.
Keywords:Fourier transform infrared spectroscopy(FTIR)  Ink  Questioned document examination  Erasable pen  Principal component analysis(PCA)  Heatmap  
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