Title :
Neural network calibration of a semiconductor metal oxide micro smell sensor
Author :
Reza Nadafi, D.B. ; Nejad, Saman Nazari ; Kabganian, Mansour ; Barazandeh, Farshad
Author_Institution :
New Technol. Res. Center, Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
A Design of a micro smell sensor based on semiconductor metal oxide method is presented. This sensor is able to recognize two different kinds of gas (CO and H2) and will estimate the amount of dominate gas in the environment. The SnO2 is employed as the key module of the sensor. A neural network calibration is applied to the sensor in order to identification of one of the two gases in an environment with complex combination of gases. The results vividly show that the sensor is able to approximate the amount of these two gases in the pool of gases.
Keywords :
calibration; gas sensors; microsensors; neural nets; SnO2; gas identification; gas sensor; neural network calibration; semiconductor metal oxide micro smell sensor; Calibration; Chemical sensors; Dielectrics and electrical insulation; Gas detectors; Gases; Hydrogen; Mechanical sensors; Neural networks; Resistance heating; Thermal sensors; Micro smell sensor; Neural Network; error Backpropagation training; gas sensing;
Conference_Titel :
Design Test Integration and Packaging of MEMS/MOEMS (DTIP), 2010 Symposium on
Conference_Location :
Seville
Print_ISBN :
978-1-4244-6636-8
Electronic_ISBN :
978-2-35500-011-9
