Extraction of Strong Periodic Time Frequency Characteristics and Regression Model for High-Speed Railway Track-Vehicle System
ID：53
Submission ID：94 View Protection：ATTENDEE
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 » [P3-2] Parallel Session 3（November 2 AM）
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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
All comments
15th August 2024 31st August 2024- Manuscript Submission
15th September 2024 - Acceptance Notification
1st October 2024 - Camera Ready Submission
1st October 2024 – Early Bird Registration
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