EconPapers    
Economics at your fingertips  
 

Computer-aided modeling of rolling-element bearing composition by adaptive neuro-fuzzy technique

Dragan Milcic, Miodrag Milcic, Vojkan Nojner and Milos Milovancevic

Physica A: Statistical Mechanics and its Applications, 2019, vol. 525, issue C, 582-586

Abstract: Rolling elements bearing are mechanical elements which should have optimal operational working as long as possible. There are many influential factors which could be analyzed for the optimal operational working of the rolling elements bearing. The main aim of the study was to perform sensitivity analysis of axial rolling-element bearing by data mining algorithm. Adaptive neuro-fuzzy inference system (ANFIS) was used for the mechanical elements ranking based on their influence on the revolution of the axial rolling-element bearing. According to the results temperature of outer ring has the highest impact on the number of revolution of the bearing. The combination of friction moment and temperature of outer ring has the highest impact on the number of revolution of the bearing.

Keywords: Sensitivity analysis; Bearing; Axial forces; Data mining (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119303553
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:525:y:2019:i:c:p:582-586

DOI: 10.1016/j.physa.2019.03.120

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:582-586