详细信息
Continuous wide spectrum odor sensing for electronic nose system ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Continuous wide spectrum odor sensing for electronic nose system
作者:Zhang, Wenli[1];Tian, Fengchun[1];Song, An[1];Zhao, Zhenzhen[2];Hu, Youwen[1];Jiang, Anyan[1]
第一作者:Zhang, Wenli
通讯作者:Tian, FC[1]
机构:[1]Chongqing Univ, Coll Commun Engn, Chongqing, Peoples R China;[2]Henan Univ Econ & Law, Coll Comp & Informat Engn, Zhengzhou, Henan, Peoples R China
第一机构:Chongqing Univ, Coll Commun Engn, Chongqing, Peoples R China
通讯机构:[1]corresponding author), Chongqing Univ, Coll Commun Engn, Chongqing, Peoples R China.
年份:2018
卷号:38
期号:2
起止页码:223-230
外文期刊名:SENSOR REVIEW
收录:;EI(收录号:20175204573449);Scopus(收录号:2-s2.0-85038812204);WOS:【SCI-EXPANDED(收录号:WOS:000426784200013)】;
基金:This work was supported by the Basic Science and Frontier Technology Special Project of Chongqing (Project No. cstc2015jcyjBX0042) and the Fundamental Research Funds for the Central Universities (Project No. 106112017CDJPT160001).
语种:英文
外文关键词:Cluster analysed; Continuous wide spectrum; E-nose system; Odor sensing; System errors
摘要:Purpose This paper aims to propose an odor sensing system based on wide spectrum for e-nose, based on comprehensive analysis on the merits and drawbacks of current e-nose. Design/methodology/approach The wide spectral light is used as the sensing medium in the e-nose system based on continuous wide spectrum (CWS) odor sensing, and the sensing response of each sensing element is the change of light intensity distribution. Findings Experimental results not only verify the feasibility and effectiveness of the proposed system but also show the effectiveness of least square support vector machine (LSSVM) in eliminating system errors. Practical implications Theoretical model of the system was constructed, and experimental tests were carried out by using NO2 and SO2. System errors in the test data were eliminated using the LSSVM, and the preprocessed data were classified by euclidean distance to centroids (EDC), k-nearest neighbor (KNN), support vector machine (SVM), LSSVM, respectively. Originality/value The system not only has the advantages of current e-nose but also realizes expansion of sensing array by means of light source and the spectrometer with their wide spectrum, high resolution characteristics which improve the detection accuracy and realize real-time detection.
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