Analysis of the influence of mean stress on the fatigue life of in-service high-speed train bogies using monitoring data

X. Wang, Yiqing Ni

Research output: Journal article publicationJournal articleAcademic researchpeer-review


The stress-life (S-N) approach is often used for fatigue life assessment of railway bogie components. It derives the stress ranges and mean stresses from cyclic strain/stress responses experienced by bogie parts generating from repeated loadings for purpose of fatigue assessment. Mean stresses in the stress responses affect the fatigue life of bogie components. Previous research has proposed several algorithms denoted "constant life diagrams" to account for the mean stress effect in the stress spectra. In this paper, the influence of mean stress on the fatigue life of high-speed train bogies is identified and examined using one-month strain monitoring data acquired during a passenger train running on a high-speed railway in China. Firstly, a method of fatigue life assessment capable of considering mean stress effect is introduced for processing the in-service monitoring data. It defines a new parameter Q based on the constant life diagrams to take into account the influence of mean stress on fatigue life. Secondly, in-service mean stresses as well as stress ranges are identified from the strain time history measured during each of the train trips. For the purpose of fatigue life assessment, the spectra of stress range, distribution of mean stress and associated Q are derived and their characteristics are examined and interpreted with statistical techniques. Finally, the distribution of the parameter Q confirms the negative influence of in-service mean stress on fatigue life. Based on the findings, an optimal process to consider stress range and mean stress for fatigue life assessment of high-speed train bogies is provided.
Original languageEnglish
JournalCivil-Comp Proceedings
Publication statusPublished - 1 Jan 2016


  • Constant life diagram
  • Fatigue life assessment
  • High-speed train bogie
  • In-service monitoring
  • Mean stress effect

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence

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