Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials

Study on Comprehensive Evaluation Method for Track Irregularity Based on HSMM

Authors
Limei Guo, Haixin Lin, Xianghua Wu, Hanyu Cui
Corresponding Author
Limei Guo
Available Online January 2016.
DOI
https://doi.org/10.2991/icsmim-15.2016.220How to use a DOI?
Keywords
Track irregularity hidden semi-Markov models track quality index multi-source track detection data.
Abstract

Evaluation of track irregularity is the foundation of track maintenance and traffic safety. A comprehensive evaluation model based on hidden semi-Markov models was proposed to evaluate track irregularity in a certain length, which used the multiple dynamic and static detection data. The model also took into account the different affection of track structure, passed total weight and allowed velocity. The features of track quality index, track complex irregularity, acceleration amplitude were extracted to train the proposed model. Finally, the effectiveness of the proposed model is verified by the simulation results.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
Series
Advances in Computer Science Research
Publication Date
January 2016
ISBN
978-94-6252-157-5
ISSN
2352-538X
DOI
https://doi.org/10.2991/icsmim-15.2016.220How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Limei Guo
AU  - Haixin Lin
AU  - Xianghua Wu
AU  - Hanyu Cui
PY  - 2016/01
DA  - 2016/01
TI  - Study on Comprehensive Evaluation Method for Track Irregularity Based on HSMM
BT  - Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
PB  - Atlantis Press
SP  - 1191
EP  - 1194
SN  - 2352-538X
UR  - https://doi.org/10.2991/icsmim-15.2016.220
DO  - https://doi.org/10.2991/icsmim-15.2016.220
ID  - Guo2016/01
ER  -