Physica2022,Vol.58615.DOI:10.1016/j.physa.2021.126454

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

Zheng, Pengjun Huang, Zhaodong Chien, Steven Zhu, Wei
Physica2022,Vol.58615.DOI:10.1016/j.physa.2021.126454

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

Zheng, Pengjun 1Huang, Zhaodong 1Chien, Steven 2Zhu, Wei3
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作者信息

  • 1. Ningbo Univ
  • 2. New Jersey Inst Technol
  • 3. Tongji Univ
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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. (C) 2021 Elsevier B.V. All rights reserved.

Key words

Urban rail transit/Wheel wear/Inspection/Maintenance/Reliability/Bayesian approach/WEAR PREDICTION/PROFILE WEAR/MODEL/CONVERGENCE/MAINTENANCE/RELIABILITY/EVOLUTION/TIMES

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出版年

2022
Physica

Physica

ISSN:0378-4371
被引量2
参考文献量42
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