Optimization of Hydrostatic Thrust Bearing Using Enhanced Grey Wolf Optimizer

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Şahin İ., Dorterler M., Gokce H.

MECHANIKA, cilt.25, sa.6, ss.480-486, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Sayı: 6
  • Basım Tarihi: 2019
  • Doi Numarası: 10.5755/j01.mech.25.6.22512
  • Dergi Adı: MECHANIKA
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.480-486
  • Anahtar Kelimeler: Hydrostatic Thrust Bearing, Grey wolf Optimiser, meta-heuristic, Enhanced GWO, engineering optimisation
  • Gazi Üniversitesi Adresli: Evet

Özet

The need for precise mechanical and tribological properties of the hydrostatic bearings has made them an interesting study topic for optimisation studies. In this paper, power-loss minimization problems of hydrostatic thrust bearings were solved through Grey Wolf Optimizer (GWO). Grey Wolf Optimizer is a meta-heuristic optimization method standing out with its successful applications in engineering design problems. Power-loss minimization problem of hydrostatic thrust bearings was applied on Grey Wolf Optimizer (GWO) for the first time. The obtained results were evaluated together with the previous studies conducted, and a detailed comparison was made. The most significant innovation of the study is the innovation made in the mathematical model of the GWO. A new model (Enhanced GWO, EGWO) that increases the variety of valid solutions was proposed. The comparisons made both with GWO and other studies in the literature show that EGWO got the best known fitness value with the highest success rate. The consistency and statistical performance of the EGWO show that this method can be used in the optimization of machine elements.