Title: On pantograph-catenary coupling vibration based on neural network finite element strategy

Authors: Zhixin Ou

Addresses: Department of Urban Rail Transit and Information Engineering, Anhui Communications Vocational and Technical College, Hefei City, Anhui Province, 230051, China

Abstract: When the traditional high-speed train pantograph-catenary system is used for the coupling parameter calculation, there exist problems of uneven mechanical vibration force, changes in parameters and model structures. Based on analysing the finite element modelling process of the pantograph-catenary system, the neural network finite element cutting method is used to optimise the overall structure of the pantograph-catenary, and a dynamic coupling equation is developed to stabilise the data. By comparing finite element control strategy based on neural network with the least squares algorithm based on model identification, neural network control strategies have better parameter tuning and fitting characteristics. The vibration frequency and error parameters of the pantograph-catenary model can be automatically adjusted to match with the set values. The experiments show that the vibration frequency of the pantograph is decreased by 5%; the overall stability is improved by 8% and the parameter coupling accuracy is increased by 30%.

Keywords: pantograph-catenary coupling system; vibration model; BP neural network; finite element strategy.

DOI: 10.1504/IJVSMT.2025.147366

International Journal of Vehicle Systems Modelling and Testing, 2025 Vol.19 No.2, pp.105 - 127

Received: 28 Aug 2024
Accepted: 03 Jan 2025
Published online: 14 Jul 2025 *

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