Abstract:In order to solve the problem that normal electronic nose (enose) can hardly detect the low concentration gas odor of parts per billion (ppb) order, an enose preconcentration scheme and three temperature compensation (TC) methods are presented in this paper. Firstly, a preconcentrator is designed to improve the detection lower limit of the enose. Then, aiming at the problem that the detection and recognition effect of the enose decreases when the gas temperature is too high after preconcentration, three TC methods are proposed, which are the multivariate regression method, the neural network regression method and the TC ensemble learning method based on the two methods. Finally, enose detection experiment on the interior decoration material ppb level gas odor in vehicle was conducted. Two materials of polyurethane (PU) leather and polyvinyl chloride (PVC) leather were used to prepare the gases to be measured in the experiment. The average recognition accuracy rates before preconcentration, after preconcentration without TC and after preconcentration using the above three TC methods are 6114%, 8064%, 9167%, 9121% and 9506%, respectively, which verifies the effectiveness of the proposed enose preconcentrator and the TC methods.