一种基于贝叶斯网络的桥式起重机故障诊断方法

Bayesian network based fault diagnosis method applicable to bridge crane

为了提高桥式起重机的故障诊断效率和及时修复率,在对桥式起重机整机模型分解的基础上,结合贝叶斯理论,利用故障树分析法构建贝叶斯网络拓扑诊断模型,提出可正反向推理的故障诊断算法,最后在Netica平台上建立桥式起重机故障诊断模型,并验证了此故障诊断方法的可行性。研究表明,基于贝叶斯网络的桥式起重机故障诊断模型能够有效提高第一故障点定位率。

To improve fault diagnosis efficiency and timely repair rate of bridge cranes,a Bayesian network topological diagnosis model is developed by using the fault tree analysis method on the basis of decomposing the model of the whole bridge crane and using the Bayesian theory. The paper presents a fault diagnosis algorithm based on forward and backward reasoning. Eventually,the fault diagnosis model of bridge crane is established on Netica platform,and the paper further validates the feasibility of the fault diagnosis method. Study indicates that the fault diagnosis model of bridge crane based on Bayesian network can help locate the first fault point more accurately.