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

Author

Listed:
  • Milcic, Dragan
  • Milcic, Miodrag
  • Nojner, Vojkan
  • Milovancevic, Milos

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.

Suggested Citation

  • Milcic, Dragan & Milcic, Miodrag & Nojner, Vojkan & Milovancevic, Milos, 2019. "Computer-aided modeling of rolling-element bearing composition by adaptive neuro-fuzzy technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 582-586.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:582-586
    DOI: 10.1016/j.physa.2019.03.120
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