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     Research Journal of Applied Sciences, Engineering and Technology


Fuzzy Logic based Model to Predict Maximum Oil-Film Pressure in Journal Bearing

1Diyar I. Ahmed, 1S. Kasolang, 2Basim A. Khidhir and 3B.F. Yousif
1Faculty of Mechanical Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
2Sulaimani Technical College, Sulaimanyah, Kurdistan Region, Iraq
3Faculty of Engineering and Surveying, University of Southern Queensland, Toowoomba, QLD, Australia
Research Journal of Applied Sciences, Engineering and Technology  2013  20:3871-3878
http://dx.doi.org/10.19026/rjaset.6.3604  |  © The Author(s) 2013
Received: January 22, 2013  |  Accepted: March 02, 2013  |  Published: November 10, 2013

Abstract

Oil-film pressure response is one of the key parameters that describe the operating conditions in hydrodynamic lubrication regimes. In the present study, a fuzzy logic model is developed to predict the maximum oil-film pressure in hydrodynamic plain journal bearing. In the development of predictive model, journal bearing parameters of rotational speed, bearing load and oil-feed pressure are considered as model independent variables. For this purpose, a number of experiments, based Box-Behnken experiment Design technique (BBD), are performed to observe the maximum oil-film pressure values. The results revealed that the model is able to predict maximum oil-film pressure adequately.

Keywords:

Fuzzy logic, hydrodynamic lubrication, journal bearing, oil-film pressure,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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