利用贝叶斯网络的注射模修模工艺方案推理  

Modification process for injection moulds based on Bayesian network

作　　者：肖五木[1] 毛宁[1] 陈庆新[1] 陈晨[1] 

机构地区：[1]广东工业大学机电工程学院,广东广州510090

出　　处：《模具工业》2008年第8期7-11,共5页Die & Mould Industry

基　　金：国家自然科学基金项目(50775042);国家科技支撑计划项目(2006BAF01A43);国家863计划CIMS项目(2007AA04Z1A8)联合资助

摘　　要：针对注射模试模中缺陷的成因分析和解决方法的选取过程过于依赖于工程师的主观经验,因而具有极大的主观性和不确定性。基于贝叶斯网络,建立了注射模修模的经验模型。实验表明,这种模型能够为修模提供有效的解决方案作参考,有利于提高修模的效率和质量。The existing analysis on the causes of moulding, and the selection of measures to solve defects occurred in the process of trial injection the problems depend much on the experiences of design engineers that may be incorrect or inaccurate. A type of empirical model based on Bayesian network was established for the modification of moulds and it proved efficient in improving the quality of modification process for moulds.

关 键 词：贝叶斯网络 模具 修模工艺 

分 类 号：TQ320[化学工程—合成树脂塑料工业] TP39[自动化与计算机技术—计算机应用技术]