Research on Chemical Weak Signal Detection Based on Stochastic Resonance Algorithm

The role of SR (Statistical Resonance) has always attracted scientists’ interest, especially in the selection of system model and signal detection. The research of SR phenomenon has penetrated into all fields of science, and its technical application is also under active research and development. When the chemical signal is particularly weak, sometimes the introduction of external noise will cause the lag of the detection signal. In this paper, we try to detect chemical weak signals based on SR algorithm. The experimental results show that the signal-to-noise ratio of small parameter signals and large parameter signals with random common frequency increases by 14.5db and 17.4db respectively. It shows that SR algorithm combined with signal compression and subsampling can quickly and effectively detect the large-parameter multi-frequency periodic components submerged in strong noise. In this paper, SR algorithm is used to adaptively adjust the system parameters of SR system in order to optimize the signal-to-noise ratio of SR output signal. It not only overcomes the lag phenomenon of weak chemical signals, but also has good adaptability to signals with different noise levels.