Risk Identification Method for High-Speed Railway Track Based on Track Quality Index and Time-Optimal Degree-Reference-Cited by-同舟云学术

Risk Identification Method for High-Speed Railway Track Based on Track Quality Index and Time-Optimal Degree

Published:2022-06 Issue:2 Volume:8 Page:
ISSN:2376-7642
Container-title:ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
language:en
Short-container-title:ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng.

Author:

Wang Xiaohui¹,Yang Jianwei²,Du Yanping³,Wang Jinhai⁴,Wang Yanxue⁵,Liu Fu¹

Affiliation:

1. Ph.D. Student, School of Civil and Transportation Engineering, Beijing Univ. of Civil Engineering and Architecture, No. 1 Zhanlanguan Rd., Xicheng District, Beijing 100044, China.

2. Professor, Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing Univ. of Civil Engineering and Architecture, No. 1 Zhanlanguan Rd., Xicheng District, Beijing 100044, China (corresponding author).

3. Professor, School of Mechanical and Electrical Engineering, Beijing Institute of Graphic Communication, 1 Xinghua St. (Section 2), Daxing District, Beijing 102600, China.

4. Postdoctoral with Research Fellow, Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing Univ. of Civil Engineering and Architecture, No. 1 Zhanlanguan Rd., Xicheng District, Beijing 100044, China.

5. Professor, Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing Univ. of Civil Engineering and Architecture, No. 1 Zhanlanguan Rd., Xicheng District, Beijing 100044, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/AJRUA6.0001218

Reference35 articles.

1. Hierarchical Bayesian modelling of rail track geometry degradation

2. Fuzzy Logic–Based Method for Risk Assessment of Belt and Road Infrastructure Projects

3. Markov-based model for the prediction of railway track irregularities

4. A Markovian-Bayesian Network for Risk Analysis of High Speed and Conventional Railway Lines Integrating Human Errors

5. Optimized railway track health monitoring system based on dynamic differential evolution algorithm

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