Presentation Details
Extraction of Strong Periodic Time Frequency Characteristics and Regression Model for High-Speed Railway Track-Vehicle System
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Updated Time：2024-10-23 10:47:41
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Oral Presentation
Start Time：2024-11-02 08:30（Asia/Shanghai）
Duration：20min
Session：P3 Parallel Session 3 »
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Abstract
In the process of evaluating the line status using vehicle dynamic response, to address the issue of significant differences in the acceleration response of different high-speed trains under the same track irregularity excitation conditions, a lightweight regression model was constructed to normalize car body acceleration inspection data. Firstly, analyze and extract the periodic characteristics of track geometry and car body acceleration through VMD algorithm. Secondly, using energy distribution, determine the strong correlation between periodic vertical acceleration of car body and track geometry. Finally, a lightweight 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 car body is at the same level.
Keywords
Vertical acceleration of the car body; Periodic feature extraction; Variational Mode Decomposition; Inspection differences; normalization
Speaker
PengNan
assistant researcher Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation LimitedSubmission Author
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Important Date
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Conference Date
Oct 31
2024
toNov 03
2024
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Sep 30 2024
Draft paper submission deadline
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Nov 12 2024
Registration deadline
Sponsored By
Anhui University
Xi’an Jiaotong University
Harbin Institute of Technology
IEEE Instrumentation & Measurement Society
Xi’an Jiaotong University
Harbin Institute of Technology
IEEE Instrumentation & Measurement Society
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