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作 者:李宏达[1] 刘春庆 郎宇博 王岩[1] LI Hong-da;LIU Chun-qing;LANG Yu-bo;WANG Yan(School of Forensic Science and Technology,Criminal Investigation Police University of China,Shenyang,110035;School of Public Security Information Technology and Information,Criminal Investigation Police University of China,Shenyang,110035)
机构地区:[1]中国刑事警察学院刑事科学技术学院,辽宁沈阳110035 [2]中国刑事警察学院公安信息技术与情报学院,辽宁沈阳110035
出 处:《火工品》2022年第4期72-76,共5页Initiators & Pyrotechnics
基 金:国家自然科学基金项目(21804140);辽宁省自然科学基金项目(2020-MS-131);辽宁“百千万人才工程”培养项目。
摘 要:为准确、快速、可视化识别爆炸案件现场TNT、PA、Tetryl 3种爆炸物种类,基于5%二苯胺乙醇溶液、60%乙二胺丙酮溶液、0.1~0.2mol/L高锰酸钾溶液、染料分子A和B构建液体传感器阵列,对3种爆炸物的待测溶液进行检测。通过采集液体传感阵列的RGB值得到3种爆炸物的指纹图谱,结合主成分分析(PCA)、分层聚类分析(HCA)、线性判别分析(LDA)模式识别方法实现了对3种爆炸物的准确区分和正确分类,识别准确率达100%。应用该方法对真实案件中15种“疑似爆炸物”进行检测,检测结果与中华人民共和国公共安全行业标准方法的检测结果一致。In order to accurately, quickly and visually identify TNT, PA and tetryl explosives at the scene of the explosion case, the liquid sensor array was constructed based on 5% diphenylamine ethanol solution, 60% ethylenediamine acetone solution,0.1~0.2mol/L potassium permanganate solution and dye molecules A and B. The solution to be tested of the 3 explosives was detected, and the RGB value of the liquid sensing array was collected to obtain the fingerprint of the 3 explosives. Combined with principal component analysis(PCA), hierarchical cluster analysis(HCA) and linear discriminant analysis(LDA) pattern recognition methods, the accurate discrimination and correct classification of 3 explosives were realized, and the recognition accuracy was 100%. This method was applied to detect 15 “suspected explosives” in real cases, and the test results are consistent with the test results of the public safety industry standard method of the People’s Republic of China.
分 类 号:TJ450.6[兵器科学与技术—火炮、自动武器与弹药工程]
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