The Quantitative Analysis to Inferior Oil with Electronic Nose Based on Adaptive Multilayer Stochastic Resonance

This study makes the three acryl glycerin polymers, oxidation three acryl glycerins, and low carbon number fatty acid as inferior oil feature index. Using double steady state stochastic resonance signal-to-noise ratio analysis methods make the quantitative analysis to inferior oil. This paper analyzes the stochastic resonance. Introduces the principle detection system structure based on adaptive multilayer stochastic resonance algorithm in inferior oil quantitativeanalysis; and make adaptive double stochastic resonance model and inferior oil as example, give the simulation and numerical analysis of this model of the system. The results show that the system can obtain more accurate quality the proportion of the inferior oil information. At the same time, this method can effectively solve the semiconductor gas sensors of the baseline drift problem. The method of stochastic resonance has a lot of application prospect in improving the system performance.