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Abstract
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Article Information:
The Quantitative Analysis to Inferior Oil with Electronic Nose Based on Adaptive Multilayer Stochastic Resonance
Hong Men, Lei Wang and Haiping Zhang
Corresponding Author: Hong Men
Submitted: 2011 July, 20
Accepted: 2011 September, 07
Published: 2011 September, 20 |
Abstract:
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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.
Key words: Electronic noses, inferior oil, quantitative analysis, stochastic resonance, , ,
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Cite this Reference:
Hong Men, Lei Wang and Haiping Zhang, . The Quantitative Analysis to Inferior Oil with Electronic Nose Based on Adaptive Multilayer Stochastic Resonance. Research Journal of Applied Sciences, Engineering and Technology, (09): 1000-1006.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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