Neural Networks Based Study of Friction Coefficient Variation in Sliding   Bearings

dc.contributor.author	Senatore, Adolfo
dc.contributor.author	Ruggiero, Alessandro
dc.contributor.author	Palade, Vasile
dc.contributor.author	Ciortan, Sorin
dc.date.accessioned	2017-11-11T18:26:09Z
dc.date.available	2017-11-11T18:26:09Z
dc.date.issued	2007
dc.identifier.issn	1221-4590
dc.identifier.uri	http://10.11.10.50/xmlui/handle/123456789/4821
dc.description	THE ANNALS OF UNIVERSITY “DUNĂREA DE JOS“ OF GALAŢI FASCICLE VIII, 2007 (XIII), ISSN 1221-4590 TRIBOLOGY	ro_RO
dc.description.abstract	The paper presents the possibility of using the neural networks approach for the analysis of friction coefficient evolution in case of sliding bearings. Several non-metallic bearing materials are investigated, both with water and emulsion as lubricant. The results show that the neural networks can be successfully used for prediction of friction coefficient evolution during bearing service. This way the working life of the bearing can be predicted with higher accuracy, leading to preventing the mechanical systems failure.	ro_RO
dc.language.iso	en	ro_RO
dc.publisher	Universitatea "Dunărea de Jos" din Galaţi	ro_RO
dc.subject	neural network	ro_RO
dc.subject	friction coefficient	ro_RO
dc.subject	sliding bearings	ro_RO
dc.subject	non-metallic materials	ro_RO
dc.title	Neural Networks Based Study of Friction Coefficient Variation in Sliding Bearings	ro_RO
dc.type	Article	ro_RO