贝叶斯网络用于屏蔽泵系统故障分析方法的研究

摘要

This paper applies Bayesian network to the system failure analysis, with an aim to improve knowledge representation of the uncertainty logic and multi-fault states in system failure analysis. A Bayesian network for shielded pump failure analysis is presented, conducting fault parameter learning, updating Bayesian network parameter based on new samples. Finally, through the Bayesian network inference, vulnerability in this system, the largest possible failure modes, and the fault probability are obtained. The powerful ability of Bayesian network to analyze system fault is illustrated by examples.%将贝叶斯网络系统故障分析方法中,旨在提高故障分析中不确定逻辑关系知识表达和多故障状态的考虑.本文构建屏蔽泵系统故障的贝叶斯网络,对网络中故障参数进行贝叶斯方法学习,在已知新样本信息时更新网络参数,最后由贝叶斯网络推理,获得屏蔽泵系统的薄弱环节和最大可能的故障模式,及其发生概率.实例证明了贝叶斯网络可作为故障分析方法,具有更强的建模分析表达能力.