The low concentration gas detection based on parameters tuning stochastic resonance

Abstract

The stochastic resonance (SR) theory provides a new method for the detection of weak signal submerged in strong noise. Aiming at the shortcomings of the existing technologies in low concentrations gas detection and the difficulties in optimising the system parameters of stochastic resonance, this paper proposed an adaptive parameters tuning algorithm and applied it in low concentrations gas detection. First, the input signal is preprocessed to satisfy the requirements of SR system, then we developed the adaptive parameters tuning algorithm to seek the maximum weighted signal-to-noise ratio (WSNR), which was used to evaluate the performance of the system. In the end, the relationship between the maximum WSNR and concentration of gas was analysed. The experiment results indicate that the proposed method is effective in low concentrations gas detection and could be expanded to other practical engineering applications.