色谱 ›› 2016, Vol. 34 ›› Issue (11): 1106-1112.DOI: 10.3724/SP.J.1123.2016.06017

• 研究论文 • 上一篇    下一篇

Fisher判别在气相色谱-质谱分析助燃剂燃烧残留物中的应用

陈振邦1, 金静2   

  1. 1. 中国人民武装警察部队学院研究生部, 河北 廊坊 065000;
    2. 中国人民武装警察部队学院消防工程系, 河北 廊坊 065000
  • 收稿日期:2016-06-12 出版日期:2016-11-08 发布日期:2016-11-03
  • 通讯作者: 金静
  • 基金资助:

    国家科技基础性工作专项(SQ2015FY3120051).

Application of Fisher discrimination in gas chromatography-mass spectrometry analysis on combustion residues of typical combustion improvers

CHEN Zhenbang1, JIN Jing2   

  1. 1. Department of Graduate Student, Chinese People's Armed Police Forces Academy, Langfang 065000, China;
    2. Department of Fire Protection Engineering, Chinese People's Armed Police Forces Academy, Langfang 065000, China
  • Received:2016-06-12 Online:2016-11-08 Published:2016-11-03
  • Supported by:

    National Scientific and Technological Foundational Work Special Project (No. SQ2015FY3120051).

摘要:

为寻找一种用于火场助燃剂燃烧残留物鉴定的更为准确、有效的模式识别方法,对7种常见助燃剂在不同载体上的燃烧残留物样品及未知送检样品进行气相色谱-质谱(GC-MS)分析测试,通过特征组分分析鉴定出未知样品中含有汽油成分。同时运用Fisher判别及PCA(主成分分析)/Fisher判别联用两种判别方法对样本数据进行了分析处理,PCA/Fisher判别联用的结果表明送检样本中含有硝基油漆稀料成分,而仅使用Fisher判别的结果表明送检样本中含有93#汽油。通过将两种分析方法所得结果与GC-MS特征组分分析的结果进行比对发现,Fisher判别能够对7种助燃剂燃烧残留物的样本实现更有效的分类,对未知样本的判别更为有效。该研究结果为火场助燃剂鉴定提供了新的数据分析手段。

关键词: Fisher判别, 气相色谱-质谱, 物证鉴定, 主成分分析, 助燃剂

Abstract:

To find out a more accurate and effective pattern recognition method for the identification of combustion residues of typical combustion improvers, gas chromatography-mass spectrometry (GC-MS) was applied to analyze the combustion residues of seven combustion improvers loaded on different carriers and one submitted sample, and gasoline was identified directly by the GC-MS analysis from the unknown specimen. Two discrimination methods, including Fisher discrimination and PCA (principal component analysis) combined with Fisher discrimination, were used for the data analysis. The results showed that nitro paint thinner was discriminated from the submitted sample by PCA combined with Fisher discrimination, while gasoline was discriminated from unidentified sample by Fisher discrimination, which was in accordance with the direct GC-MS identification result. By comparing the results obtained by these two discrimination methods, Fisher discrimination is believed to be more efficient in classification of combustion residues of the seven combustion improvers and identification of the submitted sample. The results of this study provide a new analytical method for the combustion improvers identification.

Key words: combustion improvers, evidence identification, Fisher discrimination, gas chromatography-mass spectrometry (GC-MS), principal component analysis (PCA)

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