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

Olga FilinaDepartment of Electrical Complexes and Systems, Kazan State Energy University, 420066 Kazan, RussiaNikita V. MartyushevDepartment of Materials Science, Tomsk Polytechnic University, 634050 Tomsk, RussiaBoris V. MalozyomovDepartment of Electrotechnical Complexes, Novosibirsk State Technical University, 630073 Novosibirsk, RussiaВ С ТынченкоArtificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, RussiaV A KukartsevDepartment of Materials Science and Materials Processing Technology, Polytechnical Institute, Siberian Federal University, 660041 Krasnoyarsk, RussiaK A BashmurDepartment of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, 660041 Krasnoyarsk, RussiaP P PavlovDepartment of Electrical Complexes and Systems, Kazan State Power Engineering University, 420066 Kazan, RussiaTatyana PanfilovaDepartment of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, 660041 Krasnoyarsk, Russia
2023en
ABI

Аннотация

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%.

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