The Design and Implementation of Subway Locomotive Fault Diagnosis System Based on Adaptive Particle Filter

DOI

10.2991/icsnce-16.2016.109How to use a DOI?

Keywords

Subway locomotive; Adaptive particle; Labview; Fault diagnosis; Neural network

Abstract

Targeted at general testing process and index of multiple types of subway locomotive, combining the reality of subways in Dalian, this paper used adaptive particle filter and labview to design a multipaneled detection system for subway running.Actual survey shows that inner race fault and rolling bearing fault are two main reasons that cause faults of subway locomotive,based on these above,this paper use labview technology,mainly designing the signal waveform graphs based on TVAR model,GARCH model and graphs after filtering,so as to keep a real-time monitoring of subway running conditions.It matches with Neural network to analyze real-tome datas and give a result of fault diagnosis quickly.

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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TY  - CONF
AU  - Zhenhua Wang
AU  - Zhentao Liu
AU  - Linna Xu
PY  - 2016/07
DA  - 2016/07
TI  - The Design and Implementation of Subway Locomotive Fault Diagnosis System Based on Adaptive Particle Filter
BT  - Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
PB  - Atlantis Press
SP  - 558
EP  - 564
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsnce-16.2016.109
DO  - 10.2991/icsnce-16.2016.109
ID  - Wang2016/07
ER  -