基于扩展故障树的采煤机故障诊断专家系统研究

Research on Fault Diagnosis Expert System of Shearer Based on Extended Fault Tree

针对采煤机故障诊断专家系统知识获取困难的问题,将扩展故障树分析法和专家系统相结合,提出了基于扩展故障树的采煤机故障诊断专家系统知识获取方法。在传统故障树节点上增加节点类型、重要度等信息,建立扩展故障树,并将扩展故障树中的节点信息转换成规范化表示的专家系统知识。采用广度搜索优先、深度搜索与广度搜索结合的推理机制,提高故障查找的准确率及效率。利用专家系统开发工具CLIPS,建立了采煤机故障诊断专家系统。研究表明,该系统可准确判别采煤机故障类型并提供解决方案,提高采煤机故障诊断效率。

Aiming at the difficulty in the knowledge acquisition in expert system for shearer fault diagnosis, a knowledge acquisition method was proposed based on the combination of an extended fault tree analysis and the expert system. An extended fault tree was constructed by adding some information including node types and priorities to the nodes of the classical fault tree. Then, the information of nodes in the extended fault tree was converted into the standardly-expressed knowledge for expert system. By adopting a combined reasoning mechanism including breadth-first search, a depth-first search and breadth-first search, the accuracy and efficiency of the trouble shooting can be improved. With an expert system development tool, CLIPS, an expert system for shearer fault diagnosis was constructed. Research showed that such system can accurately recognize the fault types of shearers and give responsive solution, leading to an increased efficiency in fault diagnosis.