Title: The low concentration gas detection based on parameters tuning stochastic resonance

Authors: Ji-Jun Tong; Zhen Wang; Yan-Qin Kang; Jin-Ming Jian; Xi-Shan Guo

Addresses: Faculty of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, China ' School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, China ' School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, China ' Faculty of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, China ' Faculty of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, China

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.

Keywords: bistable stochastic resonance; parameters tuning; weighted signal-to-noise ratio; WSNR; gas detection.

DOI: 10.1504/IJICT.2017.085458

International Journal of Information and Communication Technology, 2017 Vol.11 No.1, pp.1 - 11

Received: 26 Aug 2014
Accepted: 11 Oct 2014
Published online: 28 Jul 2017 *

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