本体驱动的机械设备诊断维护知识建模  

Ontology Driven Modeling of Diagnosis and Maintenance Knowledge for Mechanical Equipment

作　　者：秦大力[1,2] 于德介[1] 刘坚[1] 

机构地区：[1]湖南大学汽车车身先进设计制造国家重点实验室,长沙410082 [2]湖南农业大学,长沙410128

出　　处：《中国机械工程》2014年第14期1861-1866,共6页China Mechanical Engineering

基　　金：国家高技术研究发展计划(863计划)资助项目(2009AA04Z414);长江学者和创新团队发展计划资助项目(531105050037);广东省省部产学研合作专项资金资助项目(2009B090300312)

摘　　要：为了提高机械故障诊断的准确性与可靠性,引入了诊断维护知识的语义表示方法。通过对设备结构信息、维护经验知识以及诊断行为过程进行建模,建立了本体驱动的故障诊断推理模型。提出了设备运行状态与故障征兆之间的本体映射算法,并根据征兆空间到故障案例空间的映射关系进行实例匹配,完成了静态维护知识与动态诊断过程的统一,从而实现自动化、智能化的故障诊断与维护决策。将所建立的本体驱动的故障诊断推理模型应用于某转子故障诊断,得到了准确、实时的诊断结果。In order to improve the accuracy and reliability of mechanical fault diagnosis ,a semantic representation for diagnostic maintenance knowledge was introduced .By building the model of equip-ment structure ,empirical maintenance knowledge and diagnostic process ,an ontology driven infer-ence model of fault diagnosis was established .An ontology mapping algorithm was proposed for the mapping between the devices’ operating status and fault symptoms ,and a diagnostic instance matc-hing algorithm was proposed to map the symptom space into the fault case space .As a result ,the static maintenance knowledge and the dynamic diagnostic process were consolidated ,furthermore ,the automation and intellectualization of fault diagnosis and maintenance decisions were achieved . The proposed reasoning model was applied to a rotor fault diagnosis ,which demonstrates that the pro-posed reasoning model can get more accurate real-time diagnostic results .

关 键 词：故障诊断 本体建模 转子 诊断推理 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]