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近红外光谱在发射药成分检测中的应用
引用本文:郭志强,任芊,黄友之,董守龙.近红外光谱在发射药成分检测中的应用[J].光谱实验室,2006,23(2):187-190.
作者姓名:郭志强  任芊  黄友之  董守龙
作者单位:北京理工大学化工与环境学院2003研1班 北京市 100081
摘    要:采用傅里叶变换近红外光谱法测定发射药中外挥发分和内挥发分的含量.本文提出了一种混合算法,该算法将偏最小二乘法(PLS)和人工神经网络(ANN)结合起来,同时利用马氏距离(Mahalanobis)法对异常样品进行剔除.与传统的多元校正算法PLS和主成分回归(PCR)相比,该算法所建模型的预测精度有明显的提高.结果表明,该算法可以满足发射药成分含量的快速分析的需要.

关 键 词:近红外光谱  偏最小二乘法  人工神经网络  马氏距离  混合算法
文章编号:1004-8138(2006)02-0187-04
收稿时间:2005-09-27
修稿时间:2005-10-19

Application of Near Infrared Spectroscopy in Determination of Components of Detonator
GUO Zhi-Qiang,REN Qian,HUANG You-Zhi,DONG Shou-Long.Application of Near Infrared Spectroscopy in Determination of Components of Detonator[J].Chinese Journal of Spectroscopy Laboratory,2006,23(2):187-190.
Authors:GUO Zhi-Qiang  REN Qian  HUANG You-Zhi  DONG Shou-Long
Institution:School of Chemical Engineering and Enviromnent, Beijing Institute of Technology, Beijing 100081,P, R, China
Abstract:In this paper,a mixed algorithm was developed based on the combination of Partial Least Square(PLS) with artificial neural network(ANN) and mahalanobis-distance method to eliminate the outlier samples,and applied to the determination of contents of outer-volatile matter and inner-volatile matter in detonator by Fourier transform near-infrared(FT-NIR) spectroscopy.Compared with the classical multivariate calibration methods such as principle component regression(PCR) and PLS,the proposed algorithm performed much better,and can be used for fast analyzing of the contents of components in detonator.
Keywords:Near-Infrared Spectroscopy  Partial Least Square  Artificial Neural Network  Mahalanobis Distance  Mixed Algorithm  
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