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 .
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
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)
关键词
故障诊断
本体建模
转子
诊断推理
fault diagnosis
ontology modeling
rotor
diagnosis inference