Estimating gas concentration using a microcantilever-based electronic nose

被引:8
|
作者
Leis, John [1 ]
Zhao, Weichang [2 ,3 ]
Pinnaduwage, Lal A. [2 ,4 ]
Gehl, Anthony C. [2 ]
Allman, Steve L. [2 ]
Shepp, Allan [3 ]
Mahmud, Ken K. [3 ]
机构
[1] Univ So Queensland, Dept Elect Elect & Comp Engn, Toowoomba, Qld 4350, Australia
[2] Oak Ridge Natl Lab, Oak Ridge, TN 37831 USA
[3] Triton Syst Inc, Chelmsford, MA 01824 USA
[4] Univ Tennessee, Dept Phys, Knoxville, TN 37996 USA
关键词
Pattern recognition; Information fusion;
D O I
10.1016/j.dsp.2009.10.026
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper investigates the determination of the concentration of a chemical vapor as a function of several nonspecific microcantilever array sensors. The nerve agent dimethyl methyl phosphonate (DMMP) in parts-per-billion concentrations in binary and ternary mixtures is able to be resolved when present in a mixture containing parts-per-million concentrations of water and ethanol. The goal is to not only detect the presence of DMMP, but additionally to map the nonspecific output of the sensor array onto a concentration scale. We investigate both linear and nonlinear approaches - the linear approach uses a separate least-squares model for each component, and a nonlinear approach which estimates the component concentrations in parallel. Application of both models to experimental data indicate that both models are able to produce bounded estimates of concentration, but that the outlier performance favors the linear model. The linear model is better suited to portable handheld analyzer, where processing and memory resources are constrained. (C) 2009 Elsevier Inc. All rights reserved.
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页码:1229 / 1237
页数:9
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