【摘要】 针对目前企业内存在的故障诊断信息分散,不易共享和重用的问题,提出基于本体的故障诊断知识管理系统模型.根据故障诊断所涉及的源知识特点,建立了结构域、测试域和故障域3个异构领域本体模型,并根据各本体之间的连接关系给出了故障树生成算法,实现知识之间的共享和重用.以4L-20/8型两级空气压缩机为研究对象,开发了基于本体的故障诊断知识管理系统,该系统能为企业用户提供更精确的知识检索和诊断决策服务,为进一步的设备智能维护提供了条件.更多还原

【Abstract】 To solve the problems such as the distribution of fault diagnosis information and the difficulty of knowledge sharing and reuse,a model of ontology-based fault diagnosis knowledge management system was introduced.According to the characteristics of the knowledge resources for fault diagnosis,Structure Ontology(StrOnto),Testing Ontology(TestOnto) and Fault Ontology(FaultOnto) were constructed.The fault tree generation algorithm based on the connection of heterogeneous ontologies was put forward to achieve the goal of knowledge sharing and reuse.An ontology-based fault diagnosis knowledge management system of 4L-20/8 two-stage air compressor was established.This system can provide more precise knowledge retrieval and diagnostic decision-making services for business users.It can also provide conditions for intelligent equipment maintenance.更多还原