Low concentration gas detection method based on adaptive stochastic resonance

Abstract

The invention discloses a low concentration gas detection method based on adaptive stochastic resonance. Collected resistance signals responsive by the sensor are pretreated to obtain periodic signals with small parameters and suitable for input by a nonlinear bistable system; initial values of the system parameters and the optimizing scope are set; weighted signal-to-noise ratio is used as an effect evaluation index; the adaptive algorithm is used for searching the optimally matched system parameters; and the parameters corresponding to the maximum weighted signal-to-noise ratio are the optimal parameters of the system, and the stochastic resonance effect is at the maximum level at this moment. The invention uses the weighted signal-to-noise ratio characterized adaptive algorithm to search the optimal parameters of the bistable system, overcomes the defects of using signal-to-noise ratio and correlation coefficient as evaluation indexes of engineering signals, and restriction of difficult choosing or inaccurate choosing of system parameters of stochastic resonance, and effectively detects weak signals. The method is applied to the detection of low concentration gas, and the deterministic mixed gases with different concentration can be distinguished by comparing the maximum values of weighted signal-to-noise.

Description

technical field [0001] The invention relates to a weak signal detection method, in particular to a low-concentration gas detection method based on adaptive stochastic resonance. Background technique [0002] With the continuous deepening of research on low-concentration gas detection, more and more detection methods have emerged. Ultrasonic technology, optical interference principle, infrared absorption spectrum principle, Sagnac effect of annular light path and cavity ring-down measurement can all be applied to the measurement of low concentration. However, due to insufficient sensitivity, these measurement techniques can only be carried out under laboratory conditions, and are time-consuming, laborious, and costly, making it difficult to popularize. [0003] Stochastic resonance theory provides a new idea for weak signal detection under strong noise background. The phenomenon of stochastic resonance has attracted much attention in some fields, such as signal processing, ...

AI Technical Summary

Problems solved by technology

In specific practical applications, there is a prominent problem that the matching relationship between the input signal, noise and nonlinear system is difficult to determine an adjustment direction to reach the stochastic resonance state as soon as possible, and for the signal actually collected by the project, Gaussian white noise The statistical characteristics of the bistable system are always unknown, and the processing method of adding noise is generally not used for it. Therefore, only by adjusting the parameters of the bistable system, the system can produce a stochastic resonance effect, thereby realizing the detection of weak signals

Images