VAPOR RECOGNITION USING ORGANIC FILMS AND ARTIFICIAL NEURAL NETWORKS

Barker, PS; Chen, JR; Agbor, NE; Monkman, AP; Mars, P; Petty, MC

Abstract

Organic thin-film sensors based on the thermal evaporation and dip-coating of polyaniline, and on the Langmuir-Blodgett deposition of a vanadium porphyrin, have been fabricated. The d.c. electrical resistances of the individual elements are found to exhibit different changes on exposure to simple vapours (water, propanol, ethyl acetate and acetone). These data have been used successfully to train an artificial neural network, based on a back-propagation technique, to recognize two of the vapours.

Citation

Barker, P., Chen, J., Agbor, N., Monkman, A., Mars, P., & Petty, M. (1994). VAPOR RECOGNITION USING ORGANIC FILMS AND ARTIFICIAL NEURAL NETWORKS. Sensors and Actuators B: Chemical, 17(2), 143-147

• Journal Article Type: Article
• Publication Date: 1994-01
• Journal: Sensors and Actuators B: Chemical
• Print ISSN: 0925-4005
• Publisher: Elsevier
• Volume: 17
• Issue: 2
• Pages: 143-147
• Keywords: ELECTRONIC NOSE; DISCRIMINATION
• Public URL: https://durham-repository.worktribe.com/output/1559098