The analysis of the effects of surface roughness of shafts on journal bearings using recurrent hybrid neural network

被引：3
|
作者：
Sinanoglu, C [1 ]
机构：
[1] Erciyes Univ, Fac Engn, Dept Engn Mech, Tribol Res Lab, Kayseri, Turkey
来源：
INDUSTRIAL LUBRICATION AND TRIBOLOGY | 2004年 / 56卷 / 06期
关键词：
mechanical components; neural nets; surface texture;
D O I：
10.1108/00368790410558239
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
This paper presents an investigation for analysing the load carrying capacity of journal bearing in a variety of conditions using a proposed neural network (NN). The NN structure is very suitable for this kind of system. The network is capable of predicting the pressures of the experimental system. The network has parallel structure and fast learning capacity. It can be outlined from the results for both approaches, NN could be used to model journal bearing systems in real time applications.
引用
收藏
页码：324 / 333
页数：10
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