Application of New Forecasting Models Based on Artificial Intelligence, New Materials and New Mechanisms to Improve the Grounding System of Supports

Artem Sulimin; Aleksandr Agunov; Tamara Hmel'nickaya; Andrey Bobrov

doi:10.20295/2223-9987-2026-3-116-125

UDC 621.31

APPLICATION OF NEW FORECASTING MODELS BASED ON ARTIFICIAL INTELLIGENCE, NEW MATERIALS AND NEW MECHANISMS TO IMPROVE THE GROUNDING SYSTEM OF SUPPORTS Application of New Forecasting Models Based on Artificial Intelligence, New Materials and New Mechanisms to Improve the Grounding System of Supports

АА Аа

Published in Bulletin of scientific research results · Issue 3, 2026 · Pages 116–125 · Rubric: PROBLEMATIC OF TRANSPORT SYSTEM

DOI: https://doi.org/10.20295/2223-9987-2026-3-116-125

Received: 15.07.2026 Accepted: 30.08.2026 Published: 05.10.2026 Language of publication: RUS

Authors

Artem Sulimin

Aleksandr Agunov

Tamara Hmel'nickaya

Andrey Bobrov

Artem Sulimin

Emperor Alexander I Petersburg State Transport University Student · Russian Federation

Aleksandr Agunov

Academic degree: doctor of technical sciences

Science rang: professor

Emperor Alexander I St. Petersburg State Transport University head · Department of "Electricity supply of railways" · Russian Federation

Tamara Hmel'nickaya

Emperor Alexander I Petersburg State Transport University Master of the · “Land-Based Transport and Technological Complexes” Department · Russian Federation

Andrey Bobrov

Emperor Alexander I Petersburg State Transport University Head of the “Energy and Engineering Support” Department · Russian Federation

ABSTRACT

Objective: to improve the grounding system for AC contact network supports by developing a device for remote monitoring of the state of spark gaps and gas-discharge protection devices, as well as substantiating the use of intelligent AI agents to process diagnostic data and transition from reactive to predictive maintenance. Methods: comparative analysis of existing control methods. A constructive solution based on a short- circuit indicator is proposed, in combination with unmanned aerial vehicles and intelligent video analytics tools. Results: the proposed solution provides contactless remote diagnostics without decommissioning the equipment and does not require significant design changes. Practical significance: continuous monitoring, early detection of hidden defects and degradation processes, increased electrical safety, optimization of operating costs and reduction of the burden on the personnel of the power supply service.

KEYWORDS

grounding system, remote monitoring, short circuit indicator, digital twin, predictive maintenance

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GOST

Sulimin A. Y., Agunov A. V., Hmel'nickaya T. V., Bobrov A. A. Application of New Forecasting Models Based on Artificial Intelligence, New Materials and New Mechanisms to Improve the Grounding System of Supports // Bulletin of scientific research results. 2026. no. 3. pp. 116-125. DOI: https://doi.org/10.20295/2223-9987-2026-3-116-125. (Date of access 12.10.2026).

MLA

Artem Sulimin, Agunov A. V., Hmel'nickaya T. V., Bobrov A. A.. "Application of New Forecasting Models Based on Artificial Intelligence, New Materials and New Mechanisms to Improve the Grounding System of Supports." Bulletin of scientific research results 2026.3 (2026): 116-125. DOI: https://doi.org/10.20295/2223-9987-2026-3-116-125.

APA

Sulimin A. Y., Agunov A. V., Hmel'nickaya T. V., Bobrov A. A. (2026). Application of New Forecasting Models Based on Artificial Intelligence, New Materials and New Mechanisms to Improve the Grounding System of Supports. Bulletin of scientific research results, 2026(3), 116-125. https://doi.org/10.20295/2223-9987-2026-3-116-125

Chicago

Artem Sulimin, Agunov A. V., Hmel'nickaya T. V., Bobrov A. A.. "Application of New Forecasting Models Based on Artificial Intelligence, New Materials and New Mechanisms to Improve the Grounding System of Supports." Bulletin of scientific research results 2026, no. 3 (2026): 116-125. https://doi.org/10.20295/2223-9987-2026-3-116-125.

WIKI

{{cite journal | author = Sulimin A. Y., Agunov A. V., Hmel'nickaya T. V., Bobrov A. A. | title = Application of New Forecasting Models Based on Artificial Intelligence, New Materials and New Mechanisms to Improve the Grounding System of Supports | journal = Bulletin of scientific research results | year = 2026 | volume = 2026 | issue = 3 | pages = 116-125 | doi = 10.20295/2223-9987-2026-3-116-125 }}

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APPLICATION OF NEW FORECASTING MODELS BASED ON ARTIFICIAL INTELLIGENCE, NEW MATERIALS AND NEW MECHANISMS TO IMPROVE THE GROUNDING SYSTEM OF SUPPORTS Application of New Forecasting Models Based on Artificial Intelligence, New Materials and New Mechanisms to Improve the Grounding System of Supports

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