摘要
汽轮发电机组的故障是复杂多样的,为解决汽轮发电机组故障知识共享难、重用难,难以动态表示,欠缺推理以及不能有效地挖掘隐含知识等问题,引入本体技术,将汽轮发电机组常见的故障用本体语义表示,构建了汽轮发电机组故障诊断领域本体。针对传统汽轮发电机组故障案例推理方法单一、诊断效率低、检索条件要求高等缺陷,引入语义相似度和属性相似度算法并设计了分层检索,提出了集成本体和案例推理的汽轮发电机组故障案例检索模型,并开发了汽轮发电机组故障诊断系统的O-CBR检索模块。实例测试表明,基于本体和案例推理的汽轮发电机组故障诊断方法是可行、有效的。
The fault of turbine generator sets is complex and diverse.In order to solve the knowledge problems of turbine generator sets failure,such as difficulties in sharing,reusing,dynamic representation,lack of reasoning,and inability to effectively mine hidden knowledge etc.it presents the common faults of steam turbine generator sets based on ontology semantics.It uses ontology semantics to represent the common faults of turbo-generator sets and constructs the fault diagnosis domain ontology of turbo-generator sets.In view of the traditional steam turbine generator set,low efficiency of single case-based reasoning method,it takes the semantic similarity and attribute similarity algorithm to design a hierarchical retrieval process,puts forward the integrated ontology and case-based reasoning of turbo-generator set fault case retrieval model,and develops a fault diagnosis system of steam turbine unit O-CBR retrieval module.The test shows that the fault diagnosis method of turbine generator set based on ontology and case-based reasoning is feasible and effective.
作者
栗宇
仝灵霄
张强
Li Yu;Tong Lingxiao;Zhang Qiang(School of Mechanical and Electrical Engineering,Lanzhou University of Technology, Gansu Lanzhou, 730050, China;Taiyuan Locomotive Depot of Daqin Railway Co., Ltd., Shanxi Taiyuan, 030045, China;Beijing Vehicle Depot of Beijing Railway Administration, Beijing, 100039, China;Guangzhou Locomotive Co., Ltd., Guangdong Guangzhou, 510830, China)
出处
《机械设计与制造工程》
2020年第7期97-102,共6页
Machine Design and Manufacturing Engineering
关键词
汽轮发电机组
故障诊断
本体
案例推理
turbine generator sets
fault diagnosis
ontology
case-based reasoning
