基于神经网络专家系统的工艺推理研究——以轴类零件为例

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.%At present ,the traditional expert system technology have problems in reasoning process aspect :incomplete part informa-tion 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 mo-mentum vector-adaptive BP algorithm training network.Finally, elaborate the design and implementation of the hybrid system technology reasoning.