Abstract
This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of railway catenary systems. It combines five types of measurements related to catenary condition, namely the contact wire stagger, contact wire height, pantograph head displacement, pantograph head vertical acceleration and pantograph-catenary contact force, as inputs
based on their physical meanings and correlations. It outputs an integrated indicator of catenary condition level. The BN parameters are learned from historical measurement data. Preliminary results shows the applicable ability of the BN to integrate multiple types of parameter while make sense of the output to facilitate maintenance decision making.
based on their physical meanings and correlations. It outputs an integrated indicator of catenary condition level. The BN parameters are learned from historical measurement data. Preliminary results shows the applicable ability of the BN to integrate multiple types of parameter while make sense of the output to facilitate maintenance decision making.
Original language | English |
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Title of host publication | Proceedings of the 25th International Symposium on Dynamics of Vehicles on Roads and Tracks |
Subtitle of host publication | Rockhampton, Queensland, Australia, August 14-18, 2017 |
Editors | Maksym Spiryagin, Timothy Gordon, Colin Cole, Tim McSweeney |
Number of pages | 6 |
Publication status | Published - 2017 |
Event | 25th International Symposium on Dynamics of Vehicles on Roads and Tracks - Rockhampton, Australia Duration: 14 Aug 2017 → 18 Aug 2017 Conference number: 25 http://www.iavsd2017.org/ |
Conference
Conference | 25th International Symposium on Dynamics of Vehicles on Roads and Tracks |
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Abbreviated title | IAVSD 2017 |
Country/Territory | Australia |
City | Rockhampton |
Period | 14/08/17 → 18/08/17 |
Internet address |