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Railway track stiffness irregularities (TSI) are common in ballasted tracks and are indicative of the track's health status. These irregularities have the potential to guide predictive maintenance. This study investigates the feasibility of using axle box acceleration (ABA) to detect TSI caused by variations in ballast-sleeper support conditions. First, a 2D train-track model, a virtual track inspection (VTI) process, and a model updating procedure are introduced. Then, VTI is performed to analyze the impact of TSI on ABA signals and wheel displacement. Finally, the model updating method is employed to identify TSI. The results find that short-wavelength and large-amplitude stiffness irregularities significantly affect ABA signals. Moreover, TSI has a greater impact on vertical wheel displacement compared to ABA. The TSI identification results demonstrate that the model updating method can detect changes in ballast-sleeper stiffness with an error of less than 10%.

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A Model Updating Framework for Railway Ballasted Track Stiffness Irregularity Interference Based on the 2D Dynamic Train-Track MDOF Model

  • 会议论文

  • 发表日期：

    2025年

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  • Xiaodong Han,
  • Shaoguang Li,
  • Liangliang Cheng

摘要

Railway track stiffness irregularities (TSI) are common in ballasted tracks and are indicative of the track's health status. These irregularities have the potential to guide predictive maintenance. This study investigates the feasibility of using axle box acceleration (ABA) to detect TSI caused by variations in ballast-sleeper support conditions. First, a 2D train-track model, a virtual track inspection (VTI) process, and a model updating procedure are introduced. Then, VTI is performed to analyze the impact of TSI on ABA signals and wheel displacement. Finally, the model updating method is employed to identify TSI. The results find that short-wavelength and large-amplitude stiffness irregularities significantly affect ABA signals. Moreover, TSI has a greater impact on vertical wheel displacement compared to ABA. The TSI identification results demonstrate that the model updating method can detect changes in ballast-sleeper stiffness with an error of less than 10%.