Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network

被引：29
|
作者：
Wang, Chong [1 ]
Wang, Lide [1 ]
Chen, Huang [1 ]
Yang, Yueyi [1 ]
Li, Ye [1 ]
机构：
[1] Beijing Jiaotong Univ, Sch Elect Engn, Beijing 100044, Peoples R China
来源：
IEEE ACCESS | 2021年 / 9卷
关键词：
Train network control management system; dynamic Fault tree analysis; Bayesian network; fault diagnosis;
D O I：
10.1109/ACCESS.2020.3046681
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Train network control management system (TCMS) is an important part of the High-speed rail train. Because of the TCMS's complex and redundant structure, long-term operation environment, etc., breakdowns inevitably in the long-time running. Based on the historical fault data of the TCMS accumulated during their online service, the working principles, failure modes, and effects analysis of TCMS are researched and the dynamic fault tree (DFT) model of TCMS failure is built. Then, the dynamic fault tree model is transformed into the Bayesian network (BN) model, which can model the reliability of such types of systems. Finally, combining DFT with BN is used for fault probability estimation and reliability assessment. The results present that increasing the reliability of key modules for the TCMS would be of great help to High-speed rail train engineers in the fault diagnosis field.
引用
收藏
页码：2618 / 2632
页数：15
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