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Proposed method for choice rational combinations of the sectional speed of an electric rolling stock under the terms of the maximum mileage with preset wear of current collector stripes and the adjustment of the catenary of existing and projected sections of power supply. The principle of operation and functionality of computer software "Program for the simulation of contact force using a nonlinear autoregressive neural network with exogenous inputs" is considered.

The article explores the modeling of the interaction between the pantograph and the catenary, which is a relevant task in the development and optimization of current collection systems. The subject of the article is the modeling of the catenary, with finite element models and lumped parameter models being the most widely used approaches. Their key characteristics are highlighted: finite element models offer high accuracy but require significant computational resources, whereas lumped parameter models allow for a quicker assessment of interactions but have limitations due to their simplified representation of physical processes. The aim of this study is to improve the accuracy of modeling the interaction between pantographs and the catenary using lumped parameter models. As part of the research, an improved catenary model is proposed, in which the lumped mass is replaced with an inerter. This modification eliminates the issue of forced oscillations and enhances the accuracy of system dynamics modeling. The proposed model is implemented in MATLAB Simulink, and its validity is confirmed through correlation analysis, demonstrating better agreement between the calculated and experimental data compared to existing models. The obtained results show that the proposed approach allows for a more accurate simulation of the interaction between the pantograph and the catenary, making it a promising solution for use in the design and optimization of current collection systems in railway transport.

The heating of the pantograph panhead of an electric rolling stock is caused by the removal of the traction electric current. The increase in temperature is due to the characteristics of the catenary and conductive materials of the suspension and current collector. Current collection low quality also leads to overheating of contact materials and limits the passage of the maximum permissible long-time current when the electric locomotive moves. The uneven distribution of temperature leads to local points of overheating and an inefficient use of the surface of the contact strips. The presented graphs of the density distribution of the position of the contact wire in the plan indicate their dependence on the profile of the path section and the type of the catenary, which determine the heat distribution along the panhead. The proposed methodology of the factor analysis of the effect on the current collector's panhead heating makes it possible to determine the causes of its uneven heating and propose measures to reduce the share of influence of each factors and to provide an increase in the removal of the traction current.

The article describes themain types ofdamageinsulatorscontact network, presents statisticsfortheirfailures. Identified weaknessesin existing methodsof diagnosingsayabout the relevance ofthe problem, especially in the areasof railwaysDC. Made experimental investigationson the measurementof the electrostaticfield on theinsulator strings. Analysis of the studiesshowed that the presencein the string of faultyinsulatorsleadsto an increase inthe electrostatic fieldaround them. Proposed a technicaldevice noncontact measurementof electrostatic fieldandmethod of determining thefaultyinsulatorin the string.

The article describes how the inclination angle of a pole affects the position of contact wire relative to the level of the rail head. It is proposed to take into account a change in position of supporting constructions on the static parameters of catenary in high-speed Railways.

A method for predicting the performance of the current collection with increasing speeds using machine learning is proposed. Methods for obtaining statistically reliable data on the contact pressure of current-carrying electric rolling stock without the need for direct measurement based on design data and analysis of external factors (weather, operational) accompanying the interaction are considered.