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Journal of Modern Transportation
Article . 2011 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Communication simulation of on-board diagnosis network in high-speed Maglev trains

Authors: Zhigang Liu; Yunchang Hou; Weijie Fu;

Communication simulation of on-board diagnosis network in high-speed Maglev trains

Abstract

The on-board diagnosis network is the nervous system of high-speed Maglev trains, connecting all controller, sensors, and corresponding devices to realize the information acquisition and control. In order to study the on-board diagnosis network’s security and reliability, a simulation model for the on-board diagnosis network of high-speed Maglev trains with the optimal network engineering tool (OPNET) was built to analyze the network’s performance, such as response error and bit error rate on the network load, throughput, and node-state response. The simulation model was verified with an actual on-board diagnosis network structure. The results show that the model results obtained are in good agreement with actual system performance and can be used to achieve actual communication network optimization and control algorithms.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
gold