基于故障树分析和贝叶斯网络方法的液压举升机构故障诊断

为应对液压举升机故障原因复杂,诊断方法准确性不高等问题,提出一种基于故障树和贝叶斯网络的液压举升机故障诊断方法。首先建立液压举升机构故障树,然后将故障树转换为贝叶斯网络,利用三角模糊函数表示举升机底事件发生概率,得到底事件模糊概率,将其做为先验概率计算叶节点发生概率,进而求得根节点后验概率以及概率重要度,可快速诊断出故障点。

Fault Diagnosis of Hydraulic Lifting Mechanism Based on Fault Tree Analysis and Bayesian Network Method

In order to deal with the problems of complicated faults of hydraulic lifts and low accuracy of diagnosis methods, a fault diagnosis method of hydraulic lifts based on fault tree and Bayesian network is proposed. Firstly, the fault tree of hydraulic lifting mechanism is established, and then the fault tree is converted into a Bayesian network. The triangular fuzzy function is used to express the probability of the bottom event of the lift, and the fuzzy probability of the bottom event is obtained, which is used as the prior probability to calculate the occurrence of the leaf node probability, and then the posterior probability of the root node and the probability importance is obtained, which can quickly diagnose the fault point.