Transient response analysis of an electronic nose using multi-exponential models

The purpose of this study is to model the transient response of conductivity-based gas sensors in the context of odor recognition with an electronic nose. Commonly, only the steady-state response of the sensor is used for pattern recognition, ignoring the transient response, which conveys useful discriminatory information. The transient response is modeled as a sum of real exponential functions that represent the different decay processes that occur during sampling of the gas into the sensor chamber and adsorption of the odor compounds onto the sensing element. Four multi-exponential models are reviewed: Gardner transform, multi-exponential transient spectroscopy, Pade-Laplace and Pade-Z transforms. Validation on experimental data from an array of conducting-polymer gas sensors shows that the Pade-Laplace and Pade-Z models have better resolution capabilities than the two spectral transforms. q 1999 Elsevier Science B.V. All rights reserved.