Investigation of Rayleigh surface acoustic wave sensors for NO gas sensing applications

Author

Shen, Chi-Yen ; Yang, Jen-Pin ; Chen, Jian-Jhong ; Huang, Yu-Fong ; Wang, Shuming T. ; Hwang, Rey-Chue

Author_Institution

Dept. of Electr. Eng., I-Shou Univ., Kaohsiung, Taiwan

fYear

2011

fDate

14-16 Sept. 2011

Firstpage

1

Lastpage

3

Abstract

This paper presents the estimation of the interference of NH₃ on the detection of NO by using neural network (NN) model. The NO Rayleigh surface acoustic wave (RSAW) sensor coated with polyaniline/WO₃ (PANI/WO₃) nanocomposite was employed as the detection sensor. The data sensed by RSAW sensor was collected and implemented and the detection property of the RSAW sensor was studied at room temperature. A neural network RSAW identifier is expected to be created in order to estimate the interference of NH₃ on the NO detection of the RSAW sensor.

Keywords

Rayleigh waves; gas sensors; neural nets; nitrogen compounds; surface acoustic wave sensors; tungsten compounds; NH₃; NO; NO detection; NO gas sensing; Rayleigh surface acoustic wave sensors; WO₃; interference estimation; neural network model; polyaniline/WO₃ nanocomposite; Artificial neural networks; Gas detectors; Interference; Surface acoustic waves; Temperature sensors; NO Rayleigh surface acoustic wave; estimation; interference; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4577-0893-0

Type

conf

DOI

10.1109/ICSPCC.2011.6061568

Filename

6061568