Estimating gas concentration using a microcantilever-based electronic nose

Leis, John and Zhao, Weichang and Pinnaduwage, Lal A. and Gehl, Anthony C. and Allman, Steve L. and Shepp, Allan and Mahmud, Ken K. (2010) Estimating gas concentration using a microcantilever-based electronic nose. Digital Signal Processing: A Review Journal, 20 (4). pp. 1229-1237. ISSN 1051-2004

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Abstract

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.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Author version deposited in accordance with the copyright policy of the publisher (Elsevier).
Depositing User: Assoc Prof John Leis
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 13 Oct 2010 11:30
Last Modified: 02 Jul 2013 23:28
Uncontrolled Keywords: signal processing; electronic nose; information fusion; pattern recognition; chemical vapor; component concentration; dimethyl methylphosphonate; gas concentration; linear model; memory resources; micro-cantilevers; microcantilever arrays; nerve agents; ternary mixtures
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
09 Engineering > 0906 Electrical and Electronic Engineering > 090603 Industrial Electronics
03 Chemical Sciences > 0301 Analytical Chemistry > 030107 Sensor Technology (Chemical aspects)
Socio-Economic Objective (SEO2008): A Defence > 81 Defence > 8101 Defence > 810104 Emerging Defence Technologies
Identification Number or DOI: doi: 10.1016/j.dsp.2009.10.026
URI: http://eprints.usq.edu.au/id/eprint/6066

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