摘要
针对液压启闭机设备专业性强,故障原因复杂等特点,该研究提出了一种基于故障树建立贝叶斯网络的故障诊断方法。首先建立了液压启闭机系统的故障树,然后将故障树转化为贝叶斯网络,计算出顶事件的发生概率并运用贝叶斯网络推理对可能造成故障的原因进行重要度分析,实例表明该方法能有效克服传统故障树分析法的局限性。
Considering the uniqueness of the hydraulic hoist device and the complexity of fault cause, we put torward a failure diagnosis method based on the Bayesian Networks which is transformed from fault tree. A fault tree of the hydraulic hoist system is established and converted to the form of Bayesian Networks for calculating the occur- rence rate of the Top Event and providing the importance factor of the bottom event by the Bayesian Networks infer- ence. The way can resolve the limitation of the traditional fault tree analysis efficiently.
出处
《液压与气动》
北大核心
2015年第1期44-48,共5页
Chinese Hydraulics & Pneumatics
基金
江苏省产学研联合创新资金项目(BY2012007)
江苏省水利科技重点项目(2009041)
江苏省水利科技项目(2014027)
南通市应用研究计划(BK2012050)
关键词
液压启闭机
贝叶斯网络
故障树分析法
故障诊断
hydraulic hoist, Bayesian Networks, fault tree analysis, fault diagnosis