Dealing with humidity in the qualitative analysis of CO and NO2 using a WO3 sensor and dynamic signal processing

In this work, we analysed the effects produced by the presence of humidity on the discriminating ability of a single resistive gas sensor working under the dynamic operation mode. The gases discriminated were CO, NO, and their mixtures. The working temperature of the sensor was modulated between 190 and 380 degreesC and its dynamic response to different concentrations of CO, NO2 and CO + NO2 mixtures was monitored either at 0 or 50 % relative humidity (at 30 degreesC). Either the fast Fourier transform (FFT) or the discrete wavelet transform (DWT) was used to extract important features from the sensor response. These features were then input to different (statistical and neural) pattern recognition methods. The species considered could be discriminated with a success rate of 85.5 % using a radial basis function neural network, which is very similar to the success rate (91.1 %) reached in the classification of measurements performed in dry conditions. (C) 2003 Elsevier B.V. All rights reserved.