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To evaluate railway vertical alignment through force-based displacement estimation, a simplified three-degree-of-freedom (3-DOF) model is employed, incorporating high-pass filtering of input excitations. In vibration analysis, small uncertainties in the measurement chain, such as offsets and noise, can introduce errors that lead to non-zero mean terms. These errors become significantly magnified during the double integration of accelerations used to estimate displacements. A common approach to mitigating this issue is the application of high-pass filters, which remove constant or slowly varying low-frequency components that contribute to error accumulation during time integration. Simulation results are compared with data recorded by a dedicated track recording vehicle used for track geometry diagnosis. The aim of this study is to expand the range of sensors and methods available for railway infrastructure track condition monitoring.

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Evaluating the Feasibility of Estimating Rail Longitudinal Level Through Double Integration of Vertical Contact Forces

  • 会议论文

  • 发表日期：

    2025年

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  • Giovanni Bellacci,
  • Mani Entezami,
  • Paul Weston,
  • Niccolò Baldanzini,
  • Luca Pugi

摘要

To evaluate railway vertical alignment through force-based displacement estimation, a simplified three-degree-of-freedom (3-DOF) model is employed, incorporating high-pass filtering of input excitations. In vibration analysis, small uncertainties in the measurement chain, such as offsets and noise, can introduce errors that lead to non-zero mean terms. These errors become significantly magnified during the double integration of accelerations used to estimate displacements. A common approach to mitigating this issue is the application of high-pass filters, which remove constant or slowly varying low-frequency components that contribute to error accumulation during time integration. Simulation results are compared with data recorded by a dedicated track recording vehicle used for track geometry diagnosis. The aim of this study is to expand the range of sensors and methods available for railway infrastructure track condition monitoring.