Reliability of machine-tractor aggregates operation

Автор: Shukhanov Stanislav N., Kuzmin Aleksandr V., Boloyev Petr A.

Журнал: Инженерные технологии и системы @vestnik-mrsu

Рубрика: Машиностроение

Статья в выпуске: 1, 2020 года.

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Introduction. The development of the agro-industrial complex is impossible without creating innovative techniques and technologies. The key role in technical support of agricultural production processes is played by machine-tractor aggregates. One of their most important operational characteristics is reliability, i.e. the ability to perform specified functions, keeping over time the values of the operational indicators within the required limits. Materials and Methods. The object of the study is the reliability of machine-tractor aggregates. The methods of mathematical modeling were used for the study. The general patterns were used for special cases, taking into account the prediction of changes in parameters over time. The analytical description of machine-tractor aggregate operation reliability was based on stationary random and correlation functions. Generalized patterns were used to construct mathematical reliability models using the results of predecessor (analogue) tests. Optimal reliability of the machine-tractor aggregate operation was determined on the basis of the mathematical model of object resource. Results. There are obtained analytical dependences for the prediction of changes in reliability parameters of machine-tractor aggregate operation over time. The methods for creating reliability mathematical models are developed. Conditions affecting the functioning of the research object are determined. Discussion and Conclusion. The analysis and synthesis of research in this science field and the obtained mathematical models show that to achieve high results it is necessary to decrease the variance of factors affecting the reliability of machine-tractor aggregates.

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Operation reliability, machine-tractor aggregate, mathematical modeling, optimization of parameters, tractor

Короткий адрес: https://sciup.org/147220650

IDR: 147220650   |   DOI: 10.15507/2658-4123.030.202001.008-020

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