Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Author

Marco, Santiago ; Ortega, Arturo ; Pardo, Antonio ; Samitier, Josep

Author_Institution

Dept. d´´Electron., Barcelona Univ., Spain

Volume

47

Issue

1

fYear

1998

fDate

2/1/1998 12:00:00 AM

Firstpage

316

Lastpage

321

Abstract

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM´s) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor´s drift with an adaptive SOM has also been investigated

Keywords

air pollution measurement; array signal processing; chemioception; error compensation; gas sensors; intelligent sensors; pattern classification; self-organising feature maps; sensor fusion; tin compounds; adaptive correction; combustion gases; data fusion; electronic nose; gas classification; gas identification; gas sensor array; intelligent processing; neural networks; pattern recognition; self-organizing maps; sensor drifts; Adaptive arrays; Atmosphere; Gas detectors; Gases; Intelligent sensors; Neural networks; Self organizing feature maps; Sensor arrays; Sensor phenomena and characterization; Tin;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.728841

Filename

728841