Train dynamic response prediction method and system in the face of complex track surface irregularities

By constructing a single irregular working condition database and performing data matching, transformation, and overlay operations, the problem of low efficiency in predicting train dynamic response under complex track surfaces in existing technologies has been solved, achieving efficient train dynamic response prediction and improving computational efficiency and prediction accuracy.

CN122310784APending Publication Date: 2026-06-30CHINA RAILWAY ERYUAN ENGINEERING GROUP CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-31
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing technologies suffer from low computational efficiency when predicting the dynamic response of trains under complex track surface unevenness, making it difficult to achieve rapid response and multi-condition simulation, especially in application scenarios that require efficient assessment of the impact of complex track surface morphology.

Method used

A dynamic response database under a single irregular working condition is constructed. By matching, coordinate transformation and superposition operations, a total dynamic response data sequence under complex track surfaces is generated. Train dynamic response is predicted using pre-stored basic data, avoiding the need to rebuild the dynamic model and solve numerical integrals.

Benefits of technology

It improves computational efficiency in multi-condition simulation scenarios, ensures consistency between prediction and simulation results, and enables rapid prediction of vehicle dynamic response under complex track surface conditions.

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Abstract

This application provides a method and system for predicting train dynamic response under complex track surface irregularities, relating to the field of train dynamic response prediction technology. The method includes: constructing a dynamic response database for a single irregularity condition; receiving complex track surface geometric parameters, matching and extracting corresponding dynamic response data sequences from the dynamic response database based on these parameters; performing coordinate transformation on each extracted dynamic response data sequence according to the starting position of each irregularity event, mapping each transformed dynamic response data sequence to a unified global coordinate system; and superimposing all coordinate-transformed dynamic response data sequences in the same global coordinate system to generate a total dynamic response data sequence of the train traversing the complex track surface. This method can improve the efficiency of train dynamic response prediction in application scenarios requiring efficient assessment of the impact of complex track surface morphology.
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