【摘要】 塞拉门系统是高铁的重要组成部分，为了解决目前塞拉门系统故障诊断效率低、准确性差等问题，提出了一种基于贝叶斯网络的高铁塞拉门故障诊断方法。首先通过对塞拉门历史故障数据进行分析，构建出塞拉门的故障树模型，详细说明故障树模型向贝叶斯网络转化过程，主要包括有向无环图和条件概率表两方面内容，采用联合树算法进行网络推理，通过诊断推理完成对高铁塞拉门系统的故障诊断分析，从而快速确定故障模式与故障点。实验分析结果验证了该方法的可行性。更多还原

【Abstract】 Sliding plug door system is an important part of high-speed railway. In order to solve the problems of low efficiency and poor accuracy of current sliding plug door system fault diagnosis,a fault diagnosis method for high-speed railway sliding plug door based on Bayesian network is proposed. First,by analyzing the historical fault data of the sliding plug door,the fault tree model of the sliding plug door is constructed,and the conversion process of the fault tree model to the Bayesian network is explained in detail. It mainly includes the directed acyclic graph and the conditional probability table. The joint tree algorithm performs network reasoning,and completes the fault diagnosis analysis of the high-speed rail sliding plug door system through diagnostic reasoning,so as to quickly determine the failure mode and point of failure. The experimental analysis results verify the feasibility of the method.更多还原