System architecture of a train sensor network for ubiquitous safety monitoring (P)

Guoqiang Cai, Limin Jia, Ji'an Sun, Kun Zhang, Shuai Feng, Mingming Zheng, Mengchu Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Train safety monitoring and fault diagnosis are critically important because of the disastrous results caused by train collisions and derailments. Train safety protection sensors network is capable of autonomously monitoring the working condition and actively control faults. A number of strategically placed sensors in the vehicles form a network that can monitor various vital parameters and provide real-time prompt to train driver and dispatcher. Designing such networks faces a number of challenging tasks, as one needs to address some conflicting requirements for quick diagnosis, collaborative decision making, achieving high precision and reliability. This paper presents an on-line Train Safety Sensor Network (TSSN) architecture, discusses its hardware and software structure for ambulatory failure status monitoring. The network consists of multiple sensor layers that monitor train's electrical and mechanical activities, a train data center and a ground data analysis server. The server implements fault diagnosis based on a Fault Tree Analysis method (FTA). The results shows that the sensor network contributes to higher train safety guarantee.

Original languageEnglish (US)
Title of host publicationProceedings - SEKE 2015
Subtitle of host publication27th International Conference on Software Engineering and Knowledge Engineering
PublisherKnowledge Systems Institute Graduate School
Pages736-738
Number of pages3
ISBN (Electronic)1891706373
StatePublished - Jan 1 2015
Event27th International Conference on Software Engineering and Knowledge Engineering, SEKE 2015 - Pittsburgh, United States
Duration: Jul 6 2015Jul 8 2015

Publication series

NameProceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
Volume2015-January
ISSN (Print)2325-9000
ISSN (Electronic)2325-9086

Other

Other27th International Conference on Software Engineering and Knowledge Engineering, SEKE 2015
CountryUnited States
CityPittsburgh
Period7/6/157/8/15

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • FTA
  • Sensor network
  • Train safety

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