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ADVANCES IN INDUSTRIAL ENGINEERING AND MANAGEMENT
ISSN:2222-7059 (Print);EISSN: 2222-7067 (Online)
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Title : An Intelligent Neural Network Based Gas Detection System using Metal Oxide Gas Sensor
Author(s) : Silpi Sarkar, Aritra Dasgupta, Sunipa Roy
Author affiliation : Department of Electronics and Communication Engineering, Netaji Subhash Engineering College, Kolkata, India
Department of Electronics and Instrumentation Engineering, Netaji Subhash Engineering College, Kolkata, India
Department of Electronics and Communication Engineering, Gurunanak Institute of Technology, Kolkata, India
Corresponding author img Corresponding author at : Corresponding author img  

Abstract:
Probabilistic Neural Network (PNN) has been used to ensure the reliable evaluation of responses from Zinc Oxide (ZnO) based sensors comprising of as deposited ZnO nanoflakes. Nanoflakes were deposited on a SiO2 coated p-Si substrate by a low cost chemical deposition technique. One type of sensor structure, to investigate the effect of catalytic metal alloy electrode (Pd-Ag) was fabricated in a standard laboratory. This paper reports the development of an artificial neural network based model and a special types of neural network i.e. PNN is used for successfully recognizing different concentrations of methane with two different metal contacts. The data obtained from the sensors have been analyzed using MATLAB. PNN is based on Radial Basis function. PNN classifier has been able to detect the toxic gas with 95.2 % sensitivity.

Key words:Zinc Oxide; gas sensor; probabilistic neural network; radial basis function; MATLAB

Cite it:
Silpi Sarkar, Aritra Dasgupta, Sunipa Roy, An Intelligent Neural Network Based Gas Detection System using Metal Oxide Gas Sensor, Advances in Industrial Engineering and Management, vol. 5, no. 1, 2016, pp. 24-27, doi: 10.7508/aiem.2016.01.005

Full Text : PDF(size: 294 kB, pp. 24-27, Download times:97)

DOI : 10.7508/aiem.2016.01.005

References:

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