Selectivity of Vapour Trace Detection System

Abstract

In this article we investigate the selectivity improvements of vapor trace detection system (VPDS) built of the array of differently functionalized comb capacitive sensors and extremely sensitive integrated electronic circuits. We present some simple theoretical background, a complete detection system, calibration procedure and some measured results. To improve the selectivity, we propose to use increased number of differently modified sensors together with machine learning algorithms for more efficient pattern recognition.