农业机械学报2011，Vol.42Issue(8)：122-127,6.
基于D-S证据理论的鸡蛋新鲜度多传感器融合识别
Non-destructive Egg Freshness Recognition Using Multi-sensor Fusion Based on D- S Evidence Theory
摘要
Abstract
For the purpose of enhancing the detecting stability and the model adaptability of egg freshness by non-destructive detection method, a sensor fusion was taken by the machine vision and electronic nose in the sensor level of characteristics while D - S evidence theory was chosen as the sensor information fusion method and BP artificial neural network as the specific modeling method. An improved method that could remedy for the deficiency of D - S evidence theory was discussed. Verification results showed that the basic probability assignment of uncertainty decreased to less than 0. 01 by sensor fusion optimization. The problem of low detecting range in single sensor method has been well solved. Meanwhile, the egg freshness discriminating accuracy and stability has been improved compared with no sensor fusion situation. The average discriminating accuracy reached to 92. 6% .关键词
鸡蛋/新鲜度/D-S证据理论/多传感器融合/BP神经网络Key words
Egg/ Freshness/ D - S evidence theory/ Multi-sensor fusion/ BP neural network分类
农业科技引用本文复制引用
刘鹏,屠康,潘磊庆,张伟..基于D-S证据理论的鸡蛋新鲜度多传感器融合识别[J].农业机械学报,2011,42(8):122-127,6.基金项目
国家高技术研究发展计划(863计划)资助项目(2007AA10Z213)、江苏省科技攻关项目(BE2007320)和南京农业大学青年创新基金资助项目(Y200827) （863计划）
