Year: 2012
Type: conference-paper
Abstract: The E-nose system reported is designed to address the problem of early and distributed detection of dangerous gas mixtures. It is made of a selection of Commercial Off-The-Shelf (COTS) sensors, facing a small volume chamber, whose signals are conditioned and sampled by a multifunction board connected to a personal computer. A program, implementing efficient Support Vector Machine and least square model algorithms, executes the gas classification, the concentration estimation and warns about set risk thresholds overcoming. The system training was performed in laboratory, over a wide range of concentrations in air of: methane, hexane, pentane, and hydrogen sulfide. Other boundary conditions, such as oxygen concentration, temperature and RH are also taken into account. The overall cost of the system can be made very low, adopting an embedded architecture approach, allowing to overcome the limitations of the monitoring systems deployment inside refinery plants due to the high costs of traditional GC systems.
Source: Procedia Engineering
Authors: C. Pace, W. Khalaf, M. Latino, N. Donato, G. Neri
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2065663285