Rete算法的优化及在动车组故障知识库推理中的应用

Rete algorithm optimization and its application in EMU failure knowledge reasoning

为了解决动车组在运行途中出现的各类故障,检修段需要根据动车组发生的故障进行原因分析,并及时采取相应的解决措施.因此本文将故障知识库应用到高速铁路动车组,着重研究了基于Rete算法的推理机在知识库系统的应用,并对Rete算法进行了改进,最后利用动车组故障数据对优化前后的Rete算法进行了比较,证明了改进算法的有效性.

In order to solve all kinds of faults occurred during EMU（ electric multiple unit） running on the way,maintenance segments need to be analyzed according to the failures occurred and appropriate measures need to be taken to resolve these faults. We first apply fault knowledge base to the EMU,and focus on the reason machine which based on the Rete algorithm applying in knowledge base system. Then Rete algorithm is improved. Finally,the performances of Rete algorithm before and after optimization are compared using EMU fault data. The experimental results demonstrate the effectiveness of the improved algorithm.