Abstract
Electronic nose applications in environmental monitoring are nowadays of great interest, because of the instruments proven capability of recognizing and discriminating between a variety of different gases and odors using just a small number of sensors. We present in this paper a neural network technique to create smart models for design a smart sensor for electronic nose application. The first one, called a selector, can select exactly the nature of gas detected, the second intelligent model is a compensator, which can automatically compensate the temperature effect on sensor's response and make the response independent of variation of temperature. The third one is corrector; linearize the output response of the sensor. The electronic nose is based on Co-doped SnO2 nanofibers sensor. The method discriminates qualitatively and quantitatively between six gases.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have