Neural network modeling and fuzzy control simulation for bread-baking process

被引:0
|
作者
Kim, S [1 ]
Cho, SI [1 ]
机构
[1] SEOUL NATL UNIV, COLL AGR & LIFE SCI, DEPT AGR ENGN, SEOUL 151, SOUTH KOREA
来源
TRANSACTIONS OF THE ASAE | 1997年 / 40卷 / 03期
关键词
image processing; bread baking process; food quality; neural network; fuzzy control;
D O I
暂无
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
Three quality factors of volume, browning, and temperature were measured to develop neural network models for the bread baking process. Volume and browning changes were measured using image processing techniques. Temperature changes inside the bread were measured by K-type thermocouples Three neural network models for volume, browning and bread temperatures were developed respectively, then used for fuzzy control simulation of the oven used in the baking process. The neural network models showed a good performance for predicting temperature, volume, and browning not only after 30 s but also after 2 min. Knowledge from the experiments and an experienced operator were used to construct II rules for the fuzzy controller The simulation results showed that the developed neural networks and fuzzy controller can be used to reduce the cost for heating the oven without any loss of bread quality.
引用
收藏
页码:671 / 676
页数:6
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