Inverse wheel–rail contact force and crossing irregularity identification from measured sleeper accelerations – A model-based Green's function approach
Journal article, 2024

A novel model-based method for railway Crossing Panel Condition Monitoring (CPCM) is presented. Based on sleeper accelerations measured during wheel crossing transitions and knowledge of the crossing panel design, it is shown that it is possible to identify the ballast stiffness properties, vertical wheel–rail contact forces and vertical relative wheel–rail displacement trajectories (crossing irregularities) in the crossing panel. The method uses a multibody dynamics simulation model with a finite element representation of the track structure for evaluation of the dynamic interaction between vehicle and crossing panel. Considering the low-frequency domain where the sleeper response is not significantly affected by the influence of the irregularity due to the designed (and current state of the) crossing and wing rail geometry, the ballast condition is identified via a calibration of the distribution of ballast stiffness in the finite element model. This enables ballast stiffness identification without a priori knowledge of the crossing geometry. From the reconstructed track displacements, the wheel–rail contact forces are identified by solving an inverse problem formulated using the Green's Kernel Function Method (GKFM) that provides a direct link between the track excitation forces and the track response. Further, the irregularity induced by the crossing and wing rail geometry is estimated by taking the difference between the wheel and rail displacements during the crossing transition computed from the identified wheel–rail contact forces. By monitoring the evolving irregularity, the degradation of the crossing rails over time can be assessed. The method is verified and validated using concurrently measured sleeper accelerations and laser scanned crossing geometries from six crossing panels in situ.

Inverse problem

Irregularity identification

Green's kernel function method

Force identification

Railway crossing

Condition monitoring

Author

Marko Milosevic

Chalmers, Mechanics and Maritime Sciences (M2), Dynamics

Björn Pålsson

Chalmers, Mechanics and Maritime Sciences (M2), Dynamics

A. Nissen

Swedish Transport Administration

Jens Nielsen

Chalmers, Mechanics and Maritime Sciences (M2), Dynamics

Håkan Johansson

Chalmers, Mechanics and Maritime Sciences (M2), Dynamics

Journal of Sound and Vibration

0022-460X (ISSN) 1095-8568 (eISSN)

Vol. 589 118599

Driving research and innovation to push Europe's rail system forward (IN2TRACK3)

Swedish Transport Administration (2021/19114), 2021-01-01 -- 2023-12-31.

European Commission (EC) (EC/H2020/101012456), 2021-01-01 -- 2023-12-31.

Research into enhanced track and switch and crossing system 2 (In2Track-2)

European Commission (EC) (EC/H2020/826255), 2018-11-01 -- 2021-10-31.

Swedish Transport Administration, 2018-11-01 -- 2021-10-31.

Areas of Advance

Transport

Subject Categories

Applied Mechanics

Infrastructure Engineering

Vehicle Engineering

DOI

10.1016/j.jsv.2024.118599

More information

Latest update

8/8/2024 1