The characteristics of a “stop–flow” mode of sensor array operation using data with the best classification performance

The paper presents an approach to characterizing a “stop–flow” mode of sensor array operation. The considered operation mode involves three successive phases of sensors exposure: flow (in a stream of measured gas), stop (in zero flow conditions) and recovery (in a stream of pure air). The mode was characterized by describing the distribution of information, which is relevant for classification of measured gases in the response of sensor array. The input data for classifier were the sets of sensors output values, acquired in discrete time moments of the measurement. Discriminant Function Analysis was used for data analysis. Organic vapours of ethanol, acetic acid and ethyl acetate in air were measured and classified. Our attention was focused on data sets which allowed for 100% efficient recognition of analytes. The number, size and composition of those data sets were examined versus time of sensor array response. This methodology allowed to observe the distribution of classification-relevant information in the response of sensor array obtained in “stop–flow” mode. Hence, it provided for the characterization of this mode.