Increasing the Efficiency of Diagnostics in the Brush-Commutator Assembly of a Direct Current Electric Motor

Olga A. Filina, Nikita V. Martyushev (), Boris V. Malozyomov, Vadim Sergeevich Tynchenko, Viktor Alekseevich Kukartsev, Kirill Aleksandrovich Bashmur, Pavel P. Pavlov and Tatyana Aleksandrovna Panfilova
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Olga A. Filina: Department of Electrical Complexes and Systems, Kazan State Energy University, 420066 Kazan, Russia
Nikita V. Martyushev: Department of Materials Science, Tomsk Polytechnic University, 634050 Tomsk, Russia
Boris V. Malozyomov: Department of Electrotechnical Complexes, Novosibirsk State Technical University, 630073 Novosibirsk, Russia
Vadim Sergeevich Tynchenko: Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia
Viktor Alekseevich Kukartsev: Department of Materials Science and Materials Processing Technology, Polytechnical Institute, Siberian Federal University, 660041 Krasnoyarsk, Russia
Kirill Aleksandrovich Bashmur: Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, 660041 Krasnoyarsk, Russia
Pavel P. Pavlov: Department of Electrical Complexes and Systems, Kazan State Power Engineering University, 420066 Kazan, Russia
Tatyana Aleksandrovna Panfilova: Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, 660041 Krasnoyarsk, Russia

Energies, 2023, vol. 17, issue 1, 1-24

Abstract: Increasing the productivity and reliability of mining infrastructure facilities is an important task in achieving future goals. Mining dump trucks are an important part of coal mine infrastructure. In this article, to determine the reliability indicators in a brush–commutator unit and the residual life of electric motor brushes, a mathematical model for processing statistical data has been developed, which allows for the classification of types of failures and, unlike existing models, the determination of the life of the brushes according to the maximum extent of their wear. A method for predicting the residual life of an electric brush in a DC electric motor is presented, which contains a list of controlled reliability indicators, included a mathematical model. The described model improves the accuracy of the prediction and detection of DC motor failures. The derivation of the general formula for calculating the residual life of electric brushes is given. Based on the proposed mathematical model, we studied and calculated the reliability of the brush–commutator unit, the minimum height of the brush during operation, the average rate of its wear, the standard deviation and the mathematical expectation of brush wear. A nomogram of the failure-free operation time of the brush–commutator unit in a DC electric motor was modeled using the height of the brush during operation. Output parameters after the implementation of this monitoring system include the reliability of the electric motor operation. At the same time, diagnostic characteristics are improved twofold, and the residual life of the brush-switching unit is increased by 28–30%.

Keywords: DC electric motor; brush wear; diagnosing; commutation stability; operating modes; mining dump truck (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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