Approximation of forces of fluid film bearing lubricating layer using machine learning methods

Мұқаба

Дәйексөз келтіру

Толық мәтін

Аннотация

The article analyzes the application of various machine learning methods for solving the problem of approximating the forces of fluid film bearing lubricating layer in static formulation. The initial data on the values of lubricating layer forces for different shaft positions were obtained using a model of a rotor-bearing system based on the numerical solution of the Reynolds equation, with account for the cavitation effect. Methods for reducing the amount of calculation required to obtain the necessary data set are determined on the basis of analyzing solution approximation accuracy with artificial neural networks. After that, approximation models were constructed using a number of other machine learning methods, and the accuracy of predictions as well as the duration of the training process were analyzed. Finally, conclusions were drawn about the most effective approaches to building such models.

Авторлар туралы

Yu. Kazakov

Orel State University named after I.S. Turgenev

Хат алмасуға жауапты Автор.
Email: KazakYurii@yandex.ru

Student

Ресей

I. Stebakov

Orel State University named after I.S. Turgenev

Email: chester50796@yandex.ru

Postgraduate Student of the Department of Mechatronics, Mechanics and Robotics

Ресей

D. Shutin

Orel State University named after I.S. Turgenev

Email: rover.ru@gmail.com

Candidate of Science (Engineering), Associate Professor, Department of Mechatronics, Mechanics and Robotics

Ресей

L. Savin

Orel State University named after I.S. Turgenev

Email: savin3257@mail.ru

Doctor of Science (Engineering), Professor, Department of Mechatronics, Mechanics and Robotics

Ресей

Әдебиет тізімі

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