Design of an artificial neural network for analysis of frictional power loss of hydrostatic slipper bearings

Canbulut F., YILDIRIM Ş., SINANOGLU C.

TRIBOLOGY LETTERS, cilt.17, sa.4, ss.887-899, 2004 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 4
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1007/s11249-004-8097-6
  • Dergi Adı: TRIBOLOGY LETTERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.887-899
  • Anahtar Kelimeler: frictional power loss, neural network, hydrostatic bearing, WATER HYDRAULIC PUMPS, LUBRICATION, MOTORS, PARTS
  • Erciyes Üniversitesi Adresli: Evet

Özet

In this study, the frictional power loss of the slippers affecting the performance of axial piston pumps and motors was investigated experimentally and theoretically. The working parameters and the slipper geometry causing minimum frictional power loss were determined. The system was also modeled by an artificial neural network. As can be seen in both approaches, the proposed neural network predictor can be employed in experimental applications of such systems.