Application of Artificial Neural Networks to Calculation of Oil Film Reaction Forces and Dynamics of Rotors on Journal Bearings
Increase of energy efficiency and level of information system development of rotor machines in general requires improvement of theoretical approaches to research. In the present paper the problem of high-precision and high-performance computing programs development has been considered to simulate ro...
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2017-01-01
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Series: | International Journal of Rotating Machinery |
Online Access: | http://dx.doi.org/10.1155/2017/9196701 |
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doaj-b6c963adedb4403e9cb88716b2ba1fe72020-11-24T23:15:14ZengHindawi LimitedInternational Journal of Rotating Machinery1023-621X1542-30342017-01-01201710.1155/2017/91967019196701Application of Artificial Neural Networks to Calculation of Oil Film Reaction Forces and Dynamics of Rotors on Journal BearingsAlexey V. Kornaev0Nickolay V. Kornaev1Elena P. Kornaeva2Leonid A. Savin3Modeling of Hydromechanical Systems Research Laboratory, The Orel State University Named after I.S. Turgenev, Orel 302026, RussiaDepartment of Mechatronics and International Engineering, The Orel State University Named after I.S. Turgenev, Orel 302026, RussiaDepartment of Information Systems, The Orel State University Named after I.S. Turgenev, Orel 302026, RussiaDepartment of Mechatronics and International Engineering, The Orel State University Named after I.S. Turgenev, Orel 302026, RussiaIncrease of energy efficiency and level of information system development of rotor machines in general requires improvement of theoretical approaches to research. In the present paper the problem of high-precision and high-performance computing programs development has been considered to simulate rotor vibrations. Based on two-layer feed-forward neural networks, numerical models have been developed to calculate oil film reaction forces to solve the rotor dynamics problems. Comparison has been done of linear and nonlinear approaches to solution of rotor dynamics problems, and a qualitative evaluation has been presented of accuracy and performance of a neural network approach compared to conventional approaches to rotor dynamics.http://dx.doi.org/10.1155/2017/9196701 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alexey V. Kornaev Nickolay V. Kornaev Elena P. Kornaeva Leonid A. Savin |
spellingShingle |
Alexey V. Kornaev Nickolay V. Kornaev Elena P. Kornaeva Leonid A. Savin Application of Artificial Neural Networks to Calculation of Oil Film Reaction Forces and Dynamics of Rotors on Journal Bearings International Journal of Rotating Machinery |
author_facet |
Alexey V. Kornaev Nickolay V. Kornaev Elena P. Kornaeva Leonid A. Savin |
author_sort |
Alexey V. Kornaev |
title |
Application of Artificial Neural Networks to Calculation of Oil Film Reaction Forces and Dynamics of Rotors on Journal Bearings |
title_short |
Application of Artificial Neural Networks to Calculation of Oil Film Reaction Forces and Dynamics of Rotors on Journal Bearings |
title_full |
Application of Artificial Neural Networks to Calculation of Oil Film Reaction Forces and Dynamics of Rotors on Journal Bearings |
title_fullStr |
Application of Artificial Neural Networks to Calculation of Oil Film Reaction Forces and Dynamics of Rotors on Journal Bearings |
title_full_unstemmed |
Application of Artificial Neural Networks to Calculation of Oil Film Reaction Forces and Dynamics of Rotors on Journal Bearings |
title_sort |
application of artificial neural networks to calculation of oil film reaction forces and dynamics of rotors on journal bearings |
publisher |
Hindawi Limited |
series |
International Journal of Rotating Machinery |
issn |
1023-621X 1542-3034 |
publishDate |
2017-01-01 |
description |
Increase of energy efficiency and level of information system development of rotor machines in general requires improvement of theoretical approaches to research. In the present paper the problem of high-precision and high-performance computing programs development has been considered to simulate rotor vibrations. Based on two-layer feed-forward neural networks, numerical models have been developed to calculate oil film reaction forces to solve the rotor dynamics problems. Comparison has been done of linear and nonlinear approaches to solution of rotor dynamics problems, and a qualitative evaluation has been presented of accuracy and performance of a neural network approach compared to conventional approaches to rotor dynamics. |
url |
http://dx.doi.org/10.1155/2017/9196701 |
work_keys_str_mv |
AT alexeyvkornaev applicationofartificialneuralnetworkstocalculationofoilfilmreactionforcesanddynamicsofrotorsonjournalbearings AT nickolayvkornaev applicationofartificialneuralnetworkstocalculationofoilfilmreactionforcesanddynamicsofrotorsonjournalbearings AT elenapkornaeva applicationofartificialneuralnetworkstocalculationofoilfilmreactionforcesanddynamicsofrotorsonjournalbearings AT leonidasavin applicationofartificialneuralnetworkstocalculationofoilfilmreactionforcesanddynamicsofrotorsonjournalbearings |
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