International Journal of Scientific Engineering and Technology
  • Year: 2013
  • Volume: 2
  • Issue: 5

Recognition Capability of ANN For The Analysis of PbO-Doped Sno2 Sensor For Detection of Acetone

  • Author:
  • Tanu Bhatnagar
  • Total Page Count: 3
  • Page Number: 370 to 372

Department of ECE, Sir Padampat Singhania University, Udaipur, India. Email: tanu.ijmt27@gmail.com

Online published on 4 November, 2017.

Abstract

In the present work thick film SnO2 sensor was fabricated on a 1”x1” alumina substrate. It consists of a gas sensitive layer (SnO2) doped with PbO, a pair of electrodes underneath the gas sensing layer serving as a contact pad for sensor. Also a heater element on the backside of the substrate was printed. The sensitivity of sensor has been studied at different temperatures (1500C-3500C) upon exposure to acetone. An approach is made to measure the sensitivity of PbO-doped SnO2 by using ANN tool. Result presented in the paper shows the potential of ANN as a design tool in the area of thick film sensor.

Keywords

Artificial Neural Network, Thick film sensor, sensitivity, Radial basis function