Determination of friction coefficient at journal bearings by experimental and by means of artificial neural networks method

被引：0
|
作者：
Ünlü, Bekir Sadik [1 ]
Durmus¸, Hülya [1 ]
Meriç, Cevdet [1 ]
Atik, Enver [1 ]
机构：
[1] Celal Bayar University, Mechanical Engineering Department, 45140 Manisa, Turkey
来源：
Mathematical and Computational Applications | 2004年 / 9卷 / 03期
关键词：
Adhesion - Bearings (machine parts) - Bronze - Copper compounds - Lubrication - Neural networks - Tribology - Velocity measurement;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Knowing friction coefficient is important for determination of wear loss conditions at journal bearings. Tribological events that influence wear and its variations affect experimental results. In this study, friction coefficient at CuSn10 Bronze radial bearings has been determined by a new approach as experimental and artificial neural networks method. In experiments, effects of bearings have been examined at dry and lubricated conditions and at different loads and velocities.
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页码：399 / 408
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