现代制造工程 ›› 2017, Vol. 444 ›› Issue (9): 89-95.doi: 10.16731/j.cnki.1671-3133.2017.09.016

• 制造技术/工艺装备 • 上一篇    下一篇

基于神经网络专家系统的工艺推理研究——以轴类零件为例

付晓东1, 殷浚喆2, 毛清华1, 窦子学3   

  1. 1 燕山大学经济管理学院,秦皇岛 066004;
    2 北京航空航天大学,北京 100089;
    3 迁安市九江线材有限责任公司,唐山 064400
  • 收稿日期:2016-08-31 出版日期:2017-09-20 发布日期:2018-01-09
  • 作者简介:付晓东,硕士,研究方向为CAPP先进制造系统。殷浚喆,本科,研究方向为气动热力。毛清华,博士,教授,研究方向为先进制造系统。窦子学,本科,助理工程师,研究方向为生产工艺,计算机集成制造。E-mail:fuxiaodong2016@163.com;yinjunzhe19941005@163.com;maoqh@ysu.edu.cn;douzixue2010@163.com

Research on reasoning process based on neural network expert system—the case of shaft parts

Fu Xiaodong1, Yin Junzhe2, Mao Qinghua1, Dou Zixue3   

  1. 1 School of Economic and Management,Yanshan University,Qinhuangdao 066004,Hebei,China;
    2 Beihang University,Beijing 100089,China;
    3 Qian’an Jiujiang Wire Co.Ltd.,Tangshan 064400,Hebei,China
  • Received:2016-08-31 Online:2017-09-20 Published:2018-01-09

摘要: 目前,传统专家系统工艺推理时存在零件信息提取不完整、知识获取困难和推理能力弱的问题,采用基于神经网络和规则的混合推理机制替代传统专家系统可以解决有效上述问题。首先,运用特征技术提取零件信息,将零件信息转换为特征矩阵,作为神经网络专家系统的输入;然后,根据特征矩阵搜索推理策略,基于轴类零件特征将神经网络分为精度、形状和热处理三类子网络,采用动量-自适应学习率BP算法训练网络;最后设计与实现了混合系统工艺推理过程。

关键词: 工艺推理, 专家系统, 神经网络, 特征矩阵

Abstract: At present,the traditional expert system technology have problems in reasoning process aspect:incomplete part information extraction,knowledge acquisition and reasoning ability weakly.Use hybrid reasoning mechanism based on neural network and rule instead of traditional expert system can solve the problems.First,use feature technology to extract part information,converting it to characteristic matrix,as input of neural network expert system.Then,according to the characteristic matrix search reasoning strategy,and classify the network as accuracy,shape and heat treatment three types based on shaft parts characters,using the momentum vector-adaptive BP algorithm training network.Finally,elaborate the design and implementation of the hybrid system technology reasoning.

Key words: reasoning process, expert system, neural network, feature matrix

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