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Math. Comput. Appl. 2004, 9(3), 399-408; doi:10.3390/mca9030399

Determination of Friction Coefficient at Journal Bearings by Experimental and by Means of Artificial Neural Networks Method

Celal Bayar University, Mechanical Engineering Department, 45140 Manisa, Turkey
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Published: 1 December 2004
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Abstract

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.
Keywords: Friction Coefficient; Journal Bearing; Artificial Neural Networks Friction Coefficient; Journal Bearing; Artificial Neural Networks
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Ünlü, B.S.; Durmuş, H.K.; Meriç, C.; Atik, E. Determination of Friction Coefficient at Journal Bearings by Experimental and by Means of Artificial Neural Networks Method. Math. Comput. Appl. 2004, 9, 399-408.

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Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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