基于多传感器融合的鸡肉新鲜度检测方法  

Method of chicken freshness detection based on multi-sensor fusion

作　　者：常志勇[1,2] 陈东辉[1,2] 张凌[1] 佟月英[1] 翁小辉[3] 佟金[1,2] 

机构地区：[1]吉林大学生物与农业工程学院,长春130022 [2]吉林大学工程仿生教育部重点实验室,长春130022 [3]吉林大学机械科学与工程学院,长春132022

出　　处：《吉林大学学报（工学版）》2013年第S1期493-496,共4页Journal of Jilin University:Engineering and Technology Edition

基　　金：吉林大学基本科研业务费项目(421060212466);吉林省科技发展计划重点项目(20060217)

摘　　要：为了快捷、无损检测鸡肉新鲜度,建立了一套基于电子鼻和力学参数两种传感器以及神经网络识别技术的智能检测系统。根据鸡肉腐败机理,合理选择传感器。采用RBF神经网络作为模式识别方法。经理化试验证明系统检测鸡肉新鲜度准确率达93.65%,结果表明设计的融合系统检测鸡肉新鲜度是可行的。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.

关 键 词：鸡肉新鲜度 多传感器融合 神经网络 模式识别 

分 类 号：TS251.7[轻工技术与工程—农产品加工及贮藏工程] TP212.9[轻工技术与工程—食品科学与工程]