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Analytical Diagnostic and Control System of Energy and Mechanical Efficiency of Electric Drives

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  • Nikolay Korolev

    (Educational Center for Digital Technologies, Empress Catherine II Saint Petersburg Mining University, 2, 21 Line of Vasilyevsky Island, 199106 St. Petersburg, Russia)

Abstract

The electric drive is strategically placed in the power industry. It is exposed to wear and tear, defects, and constructional damage, as is any technical device. An information–analytical system is presented in this work. It performs the tasks of monitoring, diagnostics, general assessment of technical condition, and continuous assessment of energy and mechanical efficiency of the electric drive based on the analysis of immediate values of currents and voltages. The system modules are finished products with practical application, which are supported by experimental validation. This article contains a detailed description of the methods implemented in the system development, as well as a description of the laboratory bench and equipment used in our experiments. The information–analytical system is shown and proved on the basis of a fault reconstruction example with electric drive misalignment. According to the obtained results, recommendations for preventive control and proposals for development in this direction are formulated.

Suggested Citation

  • Nikolay Korolev, 2025. "Analytical Diagnostic and Control System of Energy and Mechanical Efficiency of Electric Drives," Energies, MDPI, vol. 18(9), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:9:p:2266-:d:1645644
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    References listed on IDEAS

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    1. Mathew Habyarimana & Abayomi A. Adebiyi, 2025. "A Review of Artificial Intelligence Applications in Predicting Faults in Electrical Machines," Energies, MDPI, vol. 18(7), pages 1-21, March.
    2. Adam Wróblewski & Pavlo Krot & Radosław Zimroz & Timo Mayer & Jyri Peltola, 2023. "Review of Linear Electric Motor Hammers—An Energy-Saving and Eco-Friendly Solution in Industry," Energies, MDPI, vol. 16(2), pages 1-28, January.
    3. Zhang, Xinfang & Zhang, Zhe & Liu, Yang & Xu, Zhigang & Qu, Xiaobo, 2024. "A review of machine learning approaches for electric vehicle energy consumption modelling in urban transportation," Renewable Energy, Elsevier, vol. 234(C).
    4. João Monteiro & Nuno Sousa & João Coutinho-Rodrigues & Eduardo Natividade-Jesus, 2024. "Challenges Ahead for Sustainable Cities: An Urban Form and Transport System Review," Energies, MDPI, vol. 17(2), pages 1-26, January.
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    1. Belsky, A.A. & Ngyen, V.T. & Sheikhi, M.H. & Starshaia, V.V., 2025. "Analysis of specifications of bifacial photovoltaic panels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 224(C).

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