Scheduling wheel inspection for sustainable urban rail transit operation: A Bayesian approach

Zhaodong Huang, Steven Chien, Wei Zhu, Pengjun Zheng

Research output: Contribution to journalArticlepeer-review

Abstract

Scheduling the wheel inspection is critical to ensure the safety and sustainability of urban rail transit (URT) operation. The common wheel inspection is conducted on a fixed-interval basis, determined by empirical practices. However, the relationship between the distance of wheel travel and wheel wearing condition subject to track alignment is uncertain. A Bayesian model is developed to schedule the timings of wheel inspections which meet the safety thresholds for sustainable train operation. In the case study, the historic wheel inspection data of a real-world URT line was collected and analyzed, which indicates that wheel reprofiling follows a Weibull distribution. The suggested wheel inspection plan by the proposed model is compared with fix-interval inspection. The results show that the inspection frequency can be significantly reduced before yielding 180,900 km wheel travel, which satisfies the wheel reliability as 0.95.

Original languageEnglish (US)
Article number126454
JournalPhysica A: Statistical Mechanics and its Applications
Volume586
DOIs
StatePublished - Jan 15 2022

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Condensed Matter Physics

Keywords

  • Bayesian approach
  • Inspection
  • Maintenance
  • Reliability
  • Urban rail transit
  • Wheel wear

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