Extracting discriminative information from the Padé-Z-transformed responses of a temperature-modulated chemoresistive sensor for gas recognition

The response patterns of a temperature-modulated chemoresistive gas sensor were transformed to multi-exponential functions which facilitated the extraction of their discriminative features for gas diagnosis. The patterns were generated for air contaminated with different concentrations of various volatile organic compounds by applying a staircase heating voltage waveform to the microheater of a tin oxide-based sensor that modulated its operating temperature in the 50–400 °C range. Padé-Z transform was utilized for the transformation, and a novel heuristic procedure facilitated the extraction of the components of the feature vectors from the transformed data. These vectors were classified by the available techniques. The method differentiated the patterns generated for methanol, ethanol, 1-propanol, 1-butanol, and acetone contaminations in the wide concentration range examined. The method was also used to separately estimate the amount of the discriminative information in various steady state and transient response features; the results are anticipated to help design more elaborate temperature-modulated sensors for gas diagnosis.