Title :
Gas identification with tin oxide sensor array and self organizing maps: adaptive correction of sensor drifts
Author :
Marco, S. ; Pardo, A. ; Ortega, A. ; Samitier, J.
Author_Institution :
Dept. Enginyeria i Mater. Electron., Barcelona Univ., Spain
Abstract :
Low cost tin oxide gas sensors are inherently nonspecific. In addition they feature several non-desirable behaviors such as slow time response, nonlinearities and long term drifts. This paper shows that the combination of a gas sensor array together with self organizing maps can solve the gas classification problems. That is, the system is able to determine the gas present in the test chamber with error rates lower than 3%. The correction of the sensor drift with an adaptative SOM has also been investigated
Keywords :
adaptive signal processing; array signal processing; error correction; feature extraction; gas sensors; measurement errors; pattern classification; self-organising feature maps; sensor fusion; tin compounds; SnO2; adaptive correction; data normalization; gas classification problems; gas identification; gas sensor array; long term drift; low cost sensors; pattern recognition strategy; principal component analysis; self organizing maps; sensor drifts; unsupervised neural nets; Adaptive arrays; Costs; Gas detectors; Gases; Hydrogen; Neural networks; Self organizing feature maps; Sensor arrays; Signal processing algorithms; Tin;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1997. IMTC/97. Proceedings. Sensing, Processing, Networking., IEEE
Conference_Location :
Ottawa, Ont.
Print_ISBN :
0-7803-3747-6
DOI :
10.1109/IMTC.1997.610256