Abstract
For a long time, urban rail transit operators have been subject to government safety issues at all levels. Moreover, with the increasing complexity of the subway car equipment, the failure rate increased accordingly. Therefore, the research of how to diagnose mechanical fault in an efficient, rapid, and accurate way is an important issue. This paper conscientiously sums up the world rail fault diagnosis technology at the present stage by summarizing and analyzing the daily employment of the equipment and the occurrence of fault. And we chose causal graph theory in this paper to establish the causal graph model of traction system which can graphically represent direct causal relationship between failures, and constrain no restriction in graphical topology.
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Qin, Y., Zhou, Y. (2016). Probabilistic Reasoning-Based Rail Train Electric Traction System Vulnerability Analysis. In: Jia, L., Liu, Z., Qin, Y., Ding, R., Diao, L. (eds) Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation. Lecture Notes in Electrical Engineering, vol 377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49367-0_78
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DOI: https://doi.org/10.1007/978-3-662-49367-0_78
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