The implementation of preconcentrator in electronic nose system to identify low concentration of vapors using neural network method

Vapor identification system having high sensitive and discriminative capabilities is much needed in various applications such as in monitoring of environmental condition, detecting of hazardous substances, and producing of flavored foods or drinks and others. Nowadays, electronic nose technology which consists of gas sensor array and neural network pattern recognition could not recognize well for the low concentration vapors. In this research, the implementation of a preconcentrator was used to increase the vapor concentration allowing the electronic nose system to gain its high sensitivity and selectivity. The experimental result showed that the electronic nose system equipped with the preconcentrator could distinguish ethanol, benzene and acetone vapors in low concentrations successfully.