Extraction of Strong Periodic Time Frequency Characteristics and Regression Model for High-Speed Railway Track-Vehicle System

To address the issue of significant differences in the acceleration response of different high-speed trains under the same track irregularity excitation conditions in the process of evaluating the line status using vehicle dynamic response, a regression model was constructed to normalize vehicle body acceleration inspection data. Firstly, analyze and extract the periodic characteristics of track geometry and vehicle body acceleration through VMD algorithm. Secondly, using energy distribution, determine the strong correlation between periodic vertical acceleration of vehicle body and track geometry. Finally, a regression model is constructed to normalize the measured acceleration data of different types of inspection vehicles. The results show that for different comprehensive inspection vehicles, the normalized vertical acceleration of the vehicle body is at the same level.

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Publication Details

Published
2024-10-31
DOI
https://doi.org/10.1109/icsmd64214.2024.10920510
Primary Topic
Railway Engineering and Dynamics
Type
article
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article

Extraction of Strong Periodic Time Frequency Characteristics and Regression Model for High-Speed Railway Track-Vehicle System

Jinzhao Liu, Nan Peng, Jinsong Yang, Qi Shao et al.
Railway Engineering and Dynamics
article

Extraction of Strong Periodic Time Frequency Characteristics and Regression Model for High-Speed Railway Track-Vehicle System

Jinzhao Liu, Nan Peng, Jinsong Yang, Qi Shao, Kai Tao, Jianfeng Guo
article en

Abstract

To address the issue of significant differences in the acceleration response of different high-speed trains under the same track irregularity excitation conditions in the process of evaluating the line status using vehicle dynamic response, a regression model was constructed to normalize vehicle body acceleration inspection data. Firstly, analyze and extract the periodic characteristics of track geometry and vehicle body acceleration through VMD algorithm. Secondly, using energy distribution, determine the strong correlation between periodic vertical acceleration of vehicle body and track geometry. Finally, a regression model is constructed to normalize the measured acceleration data of different types of inspection vehicles. The results show that for different comprehensive inspection vehicles, the normalized vertical acceleration of the vehicle body is at the same level.

China Academy of Railway Sciences (CN)
Openalex Percentile: Top 72%
Railway Engineering and Dynamics
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