Application of sensor array and neural networks for quantification of organic solvent vapours in air

Organic solvents represent significant class of air pollutants. Mixtures of butanol and aromatic compounds are classified among the most commonly used there. The concept of two sensor systems capable of measurements and analysis of butanol/xylene and butanol/toluene mixtures is presented. Sensor array consists of four commercial, tin oxide based, semiconductor type gas sensors (TGS 800 series). For the sensors characterisation manually operated gas installation is constructed. Feedforward neural networks are developed for appropriate analysis of sensors responses. Both systems provide measurements of several single compounds concentrations with inaccuracy not exceeding 15% of range. Humidity influence on system responses is rejected. Possibility of portable realisation make the systems potential replacement of traditional gas analysing devices, especially in off-laboratory applications.