Research And Implementation Of An Electronic Nose On Pattern Recognition Algorithms

Electronic nose as a mimic biological olfactory system of intelligent devices can bereliably and quickly realize the simple or complex odor discrimination.Compared with thetraditional gas chromatography and other expensive gas analysis equipment,it is sim--ple,reliable and for field testing,and therefore widely used in food,agriculture,healthcare,environment monitoring and other industries.Electronic nose system usually consists ofsensor array module,signal processing module and pattern recognition module.In the presentcase,the system hardware technology is difficult to get a big break,many researches focusedon the electronic nose pattern recognition methods of research.This paper firstly introduces the electronic nose system structure,working principle andwork processes,and then a detailed study of pattern recognition algorithms and applicationsin different fields, and the successful implementation of the program of the simulationalgorithm in the MATLAB environment.Among the many pattern recognition algorithms,this paper mainly focused on theprincipal components analysis and fuzzy neural network. Firstly,we apply the formeralgorithm to detect freshness shrimp, and get the corresponding experimental data.Throughthe analysis of a plurality of sets of experimental data,we achieve a pattern recognitionshrimp freshness in the frozen, chilled and fresh states.Secondly,we use the latter algorithmto distinguish different brands of wine.The algorithm considers the advantages of fuzzysystems and neural networks, combines the T-S fuzzy systems and neural networks to forma T-S fuzzy neural network algorithm and successfully implements pattern recognition forthe different brands of wine.The results have a certain practical significance and applicationvalue.