Vol. 200, Issue 5, May 2016, pp. 24-28

Abstract: We present in this paper a novel neural network based technique to create a model incorporates intelligence for electronic nose. The idea is to create intelligent models; the first one, called selector, can select exactly the nature of gas detected. The second intelligent model is a corrector, which can automatically compensate the electronic nose’s response characteristics and discriminating exactly the detected gas (nature and concentration), and make the response increases all time when the temperature increases. The electronic nose is based on Co-doped SnO₂ nanofiber sensor. The MATLAB environment is used during the design phase and optimization. The method discriminates qualitatively and quantitatively between six gases. The advantage of the method is that it uses a small representative database so we can easily implement the model in an electrical simulator.

Keywords: Electronic nose, EN, Gas sensor, ANN, Implementation, Selector, Corrector.

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