Analysis of the Impact of Lubrication on the Dynamic Behavior of Ball Bearings Using Artificial Neural Networks
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Abstract
Ball bearings can be found in all machines with rotary movement. Dynamic behaviour analysis of ball bearings is a phenomenon that has been studied for many years. Previous studies on the dynamic behaviour of ball bearings are based on describing the state of ball bearings using mathematical models. In addition to mathematical description, computers simulations based on finite element methods are also applied. This paper presents study of the dynamic behaviour of ball bearings using artificial neural networks. Artificial neural network models are able to predict the amplitude of vibration that will generate the analysed bearings depending on the lubrication. In this way, by the application of artificial neural networks, bearing dynamic behaviour can be predicted depending on the geometric parameters and lubrication.
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