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基于故障树贝叶斯网络的液压启闭机故障诊断方法
引用本文:杨恒乐,郭建斌.基于故障树贝叶斯网络的液压启闭机故障诊断方法[J].液压与气动,2015,0(1):44-48.
作者姓名:杨恒乐  郭建斌
作者单位:1.河海大学能源与电气学院, 江苏南京211100; 2.河海大学海洋与近海工程研究院, 江苏南京226300
基金项目: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);南通市应用研究计划(BK2012050);江苏省水利科技项目(2014027)
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。

关 键 词:液压启闭机  贝叶斯网络  故障树分析法  故障诊断  
收稿时间:2014-04-28

Fault Diagnosis Method for Hydraulic Hoist Based on Fault Tree Analysis and Bayesian Networks
YANG Heng-le,GUO Jian-bin.Fault Diagnosis Method for Hydraulic Hoist Based on Fault Tree Analysis and Bayesian Networks[J].Chinese Hydraulics & Pneumatics,2015,0(1):44-48.
Authors:YANG Heng-le  GUO Jian-bin
Affiliation:1. College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, Jiangsu211100; 2. Academy of Ocean and Offshore Engineering, Hohai University, Nanjing, Jiangsu226300
Abstract:Considering the uniqueness of the hydraulic hoist device and the complexity of fault cause, we put forward 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 occurrence rate of the Top Event and providing the importance factor of the bottom event by the Bayesian Networks inference. The way can resolve the limitation of the traditional fault tree analysis efficiently.
Keywords:
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