DocumentCode :
131648
Title :
Research on Security Assessment and Maintenance Decision of Trains Based on Bayesian Networks
Author :
Zeng Xianfeng
Author_Institution :
Guangzhou Inst. of Railway Technol., Guangzhou, China
fYear :
2014
fDate :
10-11 Jan. 2014
Firstpage :
534
Lastpage :
537
Abstract :
With the medium and low speed maglev train plays the role of commercial operation gradually, people put forward higher requirements for train safety reliability, which makes train security assessment even more prominent. Aiming at the characteristics of the maglev train equipments as well as the limitations of traditional security assessment, the establishment of a multi-state security assessment based on Bayesian network model has better diagnostic reasoning and causal reasoning ability. Finally, using the model to analysis the train traction system quantitatively, finding the weaknesses of the system and the relationship between the equipments to make rational maintenance decision. This will provide a basis to improve the reliability of train equipment and repair and maintenance work.
Keywords :
belief networks; directed graphs; magnetic levitation; maintenance engineering; railway safety; reliability; traction; Bayesian network model; causal reasoning ability; diagnostic reasoning; directed acyclic graph; low speed maglev train; maglev train equipments; multistate security assessment; rational maintenance decision; train equipment reliability; train safety reliability; train traction system; Automation; Mechatronics; Bayesian Networks; Fault Tree; Maglev Train; Maintenance Decision; Security Assessment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2014 Sixth International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4799-3434-8
Type :
conf
DOI :
10.1109/ICMTMA.2014.129
Filename :
6802747
Link To Document :
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