The analysis of the effects of surface roughness of shafts on journal bearings using recurrent hybrid neural network

Sinanoglu C.

INDUSTRIAL LUBRICATION AND TRIBOLOGY, cilt.56, sa.6, ss.324-333, 2004 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 56 Sayı: 6
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1108/00368790410558239
  • Dergi Adı: INDUSTRIAL LUBRICATION AND TRIBOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.324-333
  • Erciyes Üniversitesi Adresli: Evet

Özet

This paper presents an investigation for analysing the load carrying capacity of journal bearing in a variety of conditions using a proposed neural network (NN). The NN structure is very suitable for this kind of system. The network is capable of predicting the pressures of the experimental system. The network has parallel structure and fast learning capacity. It can be outlined from the results for both approaches, NN could be used to model journal bearing systems in real time applications.