Identification of indoor multi-component pollution gas aliasing peak based on JADE  

基于JADE的室内多组分污染气体混叠峰识别（英文）

作　　者：王芳[1] 李晋华[1] 

机构地区：[1]山西省光电信息与仪器工程技术研究中心,山西太原030051

出　　处：《Journal of Measurement Science and Instrumentation》2016年第1期24-29,共6页测试科学与仪器（英文版）

基　　金：National Natural Science Foundation of China(No.61127015)

摘　　要：Monitoring indoor harmful gas can obtain the infrared spectra of mixed harmful gases.Since the absorption bands of mixed gases overlap and their qualitative and quantitative analyses are not easy,feature extraction method based on joint approximative diagonalization of eigenmatrix（JADE）is proposed.By fully mining the hidden information of original data and analyzing higher-order statistics information of the data,each substance spectrum in the mixed gas can be accurately distinguished.In addition,a multi-dimensional data quantitative analysis model of the extracted independent source is established by using support vector machine（SVM）based on regular theory.The experimental results show that the correlation coefficients of the components of mixed gases is above 0.999 1by quantitative analysis,which verifies the accuracy of this feature extraction method.

关 键 词：aliasing peak identification joint approximative diagonalization of eigenmatrix（JADE） quantitative analysis sup-port vector machine（SVM） 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O433[自动化与计算机技术—控制科学与工程]