摘要
在油菜籽脱皮侧限排油一维冷榨试验基础上,采用半固态饱和物料和滤饼物料物理模型分别建立两个理论压榨比模型,运用Hopfeild神经网络方法识别压榨系数。识别结果表明:脱皮油菜籽在压力低于10MPa段为半固态状饱和物理模型,在压力高于20MPa段则为滤饼状物理模型,对整个压榨过程,采用分段计算物理模型可有效提高整体压榨模型精度。脱皮冷榨的压榨系数远小于未脱皮冷榨的压榨系数。
A visualization of testing apparatus has been developed to measure consolidation property of pore media under mechanical pressing. On the basis of consolidation experiments of cold pressing of rapeseed decorticated two models of pressing rate were developed, by using the physical models of semisolid saturation material and of cakes. Hopfeild neural networks were used to identify the coefficient of consolidation. The physical models of semisolid saturation material in case lower pressure(≤10 MPa) and of cakes in case high pressure(≥20 MPa) were proposed. For the sake of improving precision of mathematical simulation of uniaxial compression, the two physical models of rapeseed decorticated are used to replace single physical model in whole process of pressing. Coefficient of consolidation of cold pressing of rapeseed decorticated is far smaller than that of rapeseed.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2004年第4期125-129,共5页
Transactions of the Chinese Society of Agricultural Engineering
基金
湖北省教育厅重点科研计划项目(2002A01008)资助
武汉工业学院重点科研项目基金资助
关键词
脱皮油菜籽
压榨比
压榨系数
Hopfeild神经网络
rapeseed decorticate
pressing rate
coefficient of consolidation
Hopfeild neural networks
