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Descripción
This paper analyses the applicability of artificial neural networks for predicting the lubricated friction coefficient. We will consider their use as faster and simpler alternatives to simulations based on theoretical behaviour equations. The development of several different artificial neural networks is presented. They have been trained through tribological tests on a mini-traction-machine, which furnishes the friction coefficient in point contacts. Once the training has been completed the networks are applied as tools for predicting the results in different operating conditions. Their advantages and disadvantages are analysed compared with conventional simulation tools
Internacional	Si
JCR del ISI	No
Título de la revista	LUBRICATION SCIENCE
ISSN	1557-6833
Factor de impacto JCR
Información de impacto
Volumen
DOI	DOI: 10.1002/ls.1238
Número de revista
Desde la página	141
Hasta la página	162
Mes	SIN MES
Ranking

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• Creador: Grupo de Investigación: GI-IM: Grupo de Investigación en Ingeniería de Máquinas