Application of driving recorder to evaluate rail irregularity and vehicle swing

Ching Lung Liao, Sumei Wang, Yi Qing Ni

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Because of long distance of railway lines, it is difficult to find an appropriate method to inspect the rail condition efficiently and accurately. In this paper, a new technique based on driving recorder and image analysis is proposed to evaluate the rail condition. In line with the videos of driving recorder, three coordinate systems for train, rail, and 'observer' are defined in the Lagrangian space, respectively. The relationship between the three coordinate systems is then figured out to facilitate the identification of rail condition such as rail curvature, rail irregularity, and rail vehicle swing, etc. Based on the identified rail condition status by the proposed technique, the assessment of derailment, damage at rail fasteners, and contact condition between the wheel and rail can be conducted. In the case study, a set of videos from the driving recorders of trains during their in-service operations are analyzed by the proposed technique. The results show that the proposed technique is competent to evaluate the rail curvature, rail irregularity, vehicle swing, and train running speed accurately. Moreover, the location where the contact between the wheel and rail is abnormal can be identified by the proposed technique. It is testified that the proposed technique provides a simple and accurate way to inspect the rail condition.

Original languageEnglish
Title of host publicationStructural Health Monitoring 2019
Subtitle of host publicationEnabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
EditorsFu-Kuo Chang, Alfredo Guemes, Fotis Kopsaftopoulos
PublisherDEStech Publications Inc.
Pages2857-2863
Number of pages7
ISBN (Electronic)9781605956015
Publication statusPublished - 1 Jan 2019
Event12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019 - Stanford, United States
Duration: 10 Sep 201912 Sep 2019

Publication series

NameStructural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
Volume2

Conference

Conference12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019
Country/TerritoryUnited States
CityStanford
Period10/09/1912/09/19

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Information Management

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