Multichannel blind signal separation in semiconductor-based GAS sensor arrays

Authors:
Guillermo Bedoya;Sergi Bermejo;Joan Cabestany
Affiliations:
Department of Electronics Engineering, Technical University of Catalonia, Barcelona, Spain;Department of Electronics Engineering, Technical University of Catalonia, Barcelona, Spain;Department of Electronics Engineering, Technical University of Catalonia, Barcelona, Spain
Venue:
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Year:
2005

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Abstract

Traditional approaches to gas sensing are usually related with gas identification and classification, i.e., recognition of aromas. In this work we propose an innovative approach to determine the concentration of the single species in a gas mixture by using nonlinear source separation techniques. Additionally, responses of tin oxide sensor arrays were analyzed using nonlinear regression techniques to determine the concentrations of ammonia and acetone in gas mixtures. The use of the source separation approach allows the compensation of some of the most important sensor disadvantages: the parameter spreading and time drift.