On-site Rapid Source Identification of Drugs Based on Near-infrared Spectroscopy Technology

ZHANG Jian-qiang; LI Fan; YANG Qi-fu; HU Jun-xun; NI Chun-ming; ZHANG Xin-yu

doi:10.19969/j.fxcsxb.21120702

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On-site Rapid Source Identification of Drugs Based on Near-infrared Spectroscopy Technology

Scientific Papers | 更新时间：2022-07-15

- On-site Rapid Source Identification of Drugs Based on Near-infrared Spectroscopy Technology
- Journal of Instrumental Analysis Vol. 41, Issue 7, Pages: 1007-1013(2022)
- 作者机构：
  
  1.云南警官学院刑事侦查学院，云南昆明 650021
  2.昆明理工大学理学院，云南昆明 650500
- 作者简介：
- 基金信息：
- DOI：10.19969/j.fxcsxb.21120702
  CLC：
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张建强,李帆,杨啟富等.基于近红外光谱技术的毒品现场快速溯源研究[J].分析测试学报,2022,41(07):1007-1013.

ZHANG Jian-qiang,LI Fan,YANG Qi-fu,et al.On-site Rapid Source Identification of Drugs Based on Near-infrared Spectroscopy Technology[J].Journal of Instrumental Analysis,2022,41(07):1007-1013.
张建强,李帆,杨啟富等.基于近红外光谱技术的毒品现场快速溯源研究[J].分析测试学报,2022,41(07):1007-1013. DOI： 10.19969/j.fxcsxb.21120702.

ZHANG Jian-qiang,LI Fan,YANG Qi-fu,et al.On-site Rapid Source Identification of Drugs Based on Near-infrared Spectroscopy Technology[J].Journal of Instrumental Analysis,2022,41(07):1007-1013. DOI： 10.19969/j.fxcsxb.21120702.

摘要

毒品的日益泛滥和快速更新对缉毒部门进行现场识别和快速检测带来了巨大挑战，寻求快速、准确、低成本的现场检测方法对毒品的有效管控和案件侦破具有重要意义。该文通过使用手持式近红外光谱仪，结合粒子群优化－极限学习机（PSO－ELM）算法建立了冰毒和海洛因的现场案件快速溯源模型，并与传统的线性判别分析（LDA）算法和支持向量机（SVM）算法进行比较。结果表明：相对于传统的分类模型，该文所建立的PSO－ELM案件溯源模型能获得更好的分类结果和更高的计算效率。该方法能够实现毒品的现场快速溯源，为禁毒实战中的案件侦破提供制毒、贩毒线索。

Abstract

The increasing proliferation and quick upstate of the synthetic new drugs have brought huge challenges to the anti-narcotics units in field identification and rapid detection．It is of positive significance to seek a fast，accurate and low-cost on-site detection method for the effective control of the new drugs．In the paper，a novel particle swarm optimization－extreme learning machine（PSO－ELM） algorithm combined with a hand-held near-infrared（NIR） spectroscopy was applied to build the source recognition models for methamphetamine and heroin drugs，which was also compared with the traditional linear discriminant analysis（LDA） algorithm and support vector machine（SVM） algorithm．The experimental results showed that the PSO－ELM source recognition models could obtain the best classification results and computational efficiency．The proposed method could recognize the different sources of the drugs，provide some valuable clues for determining the nature of the case in the prohibition of actual combat．

关键词

近红外光谱（NIR）毒品极限学习机（ELM）溯源

Keywords

near-infrared spectroscopy（NIR）drugsextreme learning machine（ELM）source recognition

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