Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network
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 accumula...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9302584/ |
| _version_ | 1818579479108255744 |
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| author | Chong Wang Lide Wang Huang Chen Yueyi Yang Ye Li |
| author_facet | Chong Wang Lide Wang Huang Chen Yueyi Yang Ye Li |
| author_sort | Chong Wang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-16T07:02:21Z |
| format | Article |
| id | doaj.art-1cb07d9c458f406a97e35eae0ce7a91f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T07:02:21Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1cb07d9c458f406a97e35eae0ce7a91f2022-12-21T22:40:08ZengIEEEIEEE Access2169-35362021-01-0192618263210.1109/ACCESS.2020.30466819302584Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian NetworkChong Wang0https://orcid.org/0000-0001-9515-8916Lide Wang1https://orcid.org/0000-0002-0230-5321Huang Chen2https://orcid.org/0000-0001-9912-8925Yueyi Yang3https://orcid.org/0000-0001-5966-8169Ye Li4https://orcid.org/0000-0002-4392-7135School of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaTrain 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.https://ieeexplore.ieee.org/document/9302584/Train network control management systemdynamic Fault tree analysisBayesian networkfault diagnosis |
| spellingShingle | Chong Wang Lide Wang Huang Chen Yueyi Yang Ye Li Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network IEEE Access Train network control management system dynamic Fault tree analysis Bayesian network fault diagnosis |
| title | Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network |
| title_full | Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network |
| title_fullStr | Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network |
| title_full_unstemmed | Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network |
| title_short | Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network |
| title_sort | fault diagnosis of train network control management system based on dynamic fault tree and bayesian network |
| topic | Train network control management system dynamic Fault tree analysis Bayesian network fault diagnosis |
| url | https://ieeexplore.ieee.org/document/9302584/ |
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