System architecture of a train sensor network for automatic train safety monitoring. (January 2019)

• Record Type: Journal Article
• Authors: Cai, Guoqiang; Zhao, Jiaqing; Song, Qiong; Zhou, Mengchu
• Is Part Of: Computers & industrial engineering. Volume 127(2019)
• Page Start: 1183
• Page End: 1192
• Publication Date: 2019-01
• Subjects: Train safety -- Sensor network -- Fault diagnosis -- FTA -- Reliability analysis; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.04.038
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: An on-line Train Safety Sensor Network (TSSN) is proposed. TSSN integrates vehicles' information based on inter-vehicle connection. The server implements fault diagnosis of TSSN is based on a FTA method. TSSN can analysis reliability of real-time operating critical system in the train. 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.