吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 493-496.

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Method of chicken freshness detection based on multi-sensor fusion

CHANG Zhi-yong1,2, CHEN Dong-hui1,2, ZHANG Ling1, TONG Yue-ying1, WENG Xiao-hui3, TONG Jin1,2   

  1. 1. College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China;
    2. Key Laboratory of Bionic Engineering, Ministry of Education, Changchun 130022, China;
    3. College of Mechanical Science and Engineering, Jilin University, Changchun 130022, China
  • Received:2012-06-30 Published:2013-06-01

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Abstract:

In order to evaluate poultry freshness in a quick and non-destructive way, an intelligent inspection system was established based on neural network recognition technique and two types of sensors, including electronic nose and mechanical parameters. Sensors were chosen according to chicken deteriorate mechanism. RBF neural network was used as method of pattern recognition. The accuracy of the system for chicken freshness detection is up to 96.45% through physico-chemical examination. The experimental results indicate that it is feasible to integrate multiple sensors for chicken freshness detection.

Key words: chicken freshness, multi-sensor fusion, neural network, pattern necognition

CLC Number: 

  • TG156

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