System architecture of a train sensor network for automatic train safety monitoring

Guoqiang Cai, Jiaqing Zhao, Qiong Song, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Train safety monitoring and fault diagnosis are critically to prevent the disastrous accidents caused by train failure. Train safety protection sensor network is a modern equipment capable of autonomously monitoring working condition and actively control emergent faults. It strategically places a group of specialized sensors in the vehicles that can record various vital parameters and real-time prompt calculated error code to train driver or dispatcher. This approach also reduces operation expenses by tracing subsystems' reliability, availability and maintainability. 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 a novel online Train Safety Sensor Network (TSSN) architecture installed on train emphasis on safety monitoring and diagnostic issues. TSSN consists of multiple sensor layers that monitor train's electrical and mechanical activities, a train data center and a ground data analysis server. TSSN is modular, flexible and able to meet the required safety specification. The hardware and software structure are characterized by lower development costs compared with other market solutions. The server implements fault diagnosis based on a Fault Tree Analysis method (FTA) for a door system. The results show that the sensor network contributes to improve train safety guarantee function.

Original languageEnglish (US)
Pages (from-to)1183-1192
Number of pages10
JournalComputers and Industrial Engineering
Volume127
DOIs
StatePublished - Jan 2019

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)

Keywords

  • FTA
  • Fault diagnosis
  • Reliability analysis
  • Sensor network
  • Train safety

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