Identifying Parametric Models Used to Estimate Track Irregularities of a High-Speed Railway

This study aims to identify parametric models to estimate track irregularities in high-speed railways with simple acceleration measurements. The primary contribution of current research is the development of effective parametric models with smaller parameters. These parameters are derived from the m...

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Bibliographic Details
Published in:Machines (Basel) 2023-01, Vol.11 (1), p.6
Main Author: Choi, Sunghoon
Format: Article
Language:English
Subjects:
Acceleration
Accelerometers
Adaptive algorithms
adaptive Kalman filter
Adaptive systems
Algorithms
Geometry
High speed rail
IIR model
Inspection
Irregularities
Kalman filters
Mathematical models
Parameters
parametric models
Parametric statistics
Railway tracks
Sensors
system identification
track irregularities
Trains
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Summary:This study aims to identify parametric models to estimate track irregularities in high-speed railways with simple acceleration measurements. The primary contribution of current research is the development of effective parametric models with smaller parameters. These parameters are derived from the measured data via a specialized track geometry inspection system. An adaptive Kalman filter algorithm, using the displacement estimated from the acceleration signals as the input and measured track irregularities as the output, is applied to obtain the model’s unknown parameters. These models are applied to acceleration measured from high-speed rail vehicles in operation, and track irregularities are estimated in spatial and wavelength domains. The estimated irregularities are compared to the track geometry inspection system’s results.
ISSN:2075-1702
2075-1702
DOI:10.3390/machines11010006