A Noise Spectroscopy-Based Features Extraction Method to Detect Two Gases Using One Single MOX Sensor

Abstract

Metal oxide gas sensors have enabled gas and vapor detection with high sensitivity. However, this type of sensor suffer from lack of selectivity. Noise spectroscopy is one of solution to improve the selectivity. In this paper, we propose a technique based on using low-frequency noise to extract new features, which form unique gas signatures. By applying the recent developed noise spectroscopy-based gas identifying methods, we show the possibility of each gas signatures to discriminate gases. Noise measurements have been performed on tungsten trioxide (WO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> )-based gas sensor exposed to several NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> concentrations in dry air. The obtained results have demonstrated that a selective sensing of the studied gases is possible using a single MOX gas micro-sensor.