摘要
为了实现对拉曼光谱图的最优化处理,改善检测效果,提高鉴定效率,实现对案发现场保险杠碎片的快速无损检验鉴定,本研究借助牛顿插值多项式、Savitzky-Golay平滑滤波和Bayes判别分析的方法对保险杠样本的光谱图进行分析处理。采集6种品牌共计80个车用保险杠样本的拉曼光谱图,借助牛顿插值法、Savitzky-Golay滤波拟合法等方法处理后建立Bayes判别分类模型。结果表明:1次牛顿插值多项式处理后各样本的判别分析准确率最高,能够达到90.1%,对其开展5点Savitzky-Golay算法平滑处理后判别分析准确率可提升到97.5%。综上所述,借助牛顿插值多项式及Savitzky-Golay处理后进行判别分析可以对保险杠样本的品牌进行快速、无损、准确的检验鉴别,此方法对于其他物证的分类和鉴定也具有一定的借鉴意义。
In order to optimize the processing of Raman spectrum,improve the detection effect,improve the efficiency of identification,and realize the rapid inspection and identification of vehicle bumper debris at the crime scene,In this study,Newton interpolation polynomials,Savitzky-Golay smoothing filter and Bayes discriminant analysis were used to analyze the spectrum of vehicle bumper.80 samples of automobile bumpers from six brands were collected and processed by Newton interpolation and Savitzky-Golay filter fitting method to establish a discrimination model in the research.The results showed that the accuracy of discriminant analysis is 90.1%after one-time Newton interpolation polynomial processing,and 97.5%after five points Savitzky-Golay algorithm smoothing.In conclusion,the discrimination analysis of the whole band Raman spectrogram processed by Newton interpolation polynomial and Savitzky-Golay algorithm can be used for fast,nondestructive and accurate inspection and identification of the automobile bumper brand.This method also has certain reference significance for the classification and identification of other physical evidences.
作者
刘富邦
王继芬
汪生军
李昊轩
高春芳
何欣龙
LIU Fu-bang;WANG Ji-fen;WANG Sheng-jun;LI Hao-xuan;GAO Chun-fang;HE Xin-long(School of investigation and Forensic Science,People’s Public Security University of China,Beijing,100038,China;Traffic Police Brigade,Yongjing County,Gansu Province,Yongjing 731600,China)
出处
《化学研究与应用》
CAS
CSCD
北大核心
2020年第10期1847-1852,共6页
Chemical Research and Application
基金
2020年中国人民公安大学基本科研业务费重点项目(2020JKF206)资助。
作者简介
联系人:王继芬(1964-),女,教授,硕士生导师,主要从事微量物证与毒物毒品分析方面的研究工作。E-mail:wangjifen58@126.com。
