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Journals / Mathematical and Computational Applications / 2004 / Cilt: 9 - Sayı: 3

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

Bekir Sadık ÜNLÜ
Kaçar Hülya DURMUŞ
Cevdet MERİÇ
Enver ATİK
Pages
399–408
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In experiments, effects of bearings have been examined at dry and lubricated conditions and at different loads and velocities.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Knowing friction coefficient is important for determination of wear loss conditions at journal bearings.
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Key Findings & Data:In this study, friction coefficient at CuSnl0 Bronze radial bearings has been determined by a new approach as experimental and artificial neural networks method.
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Conclusion & Impact:In experiments, effects of bearings have been examined at dry and lubricated conditions and at different loads and velocities.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

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 CuSnl0 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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Cite This Article

ÜNLÜ, B. S., DURMUŞ, K. H., MERİÇ, C., ATİK, E. (2004). Determination of friction coefficient at journal bearings by experimental and by means of artificial neural networks method. Mathematical and Computational Applications, Cilt: 9 - Sayı: 3, 399–408. https://ajindex.com/articles/280464

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References (2)

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