Design of artificial neural networks for rotor dynamics analysis of rotating machine systems

Taplak H., Uzmay I., Yildirim S.

JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH, cilt.64, sa.6, ss.411-419, 2005 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 64 Sayı: 6
  • Basım Tarihi: 2005
  • Dergi Adı: JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.411-419
  • Erciyes Üniversitesi Adresli: Evet

Özet

A neural network predictor is designed for analyzing vibration parameters of the rotating system. The vibration parameters (amplitude, velocity, acceleration in vertical direction) are measured at the bearing points. The system's vibration and noise are analyzed with and without load. The designed neural predictor has three (input, hidden, Output) layers. In the hidden layer, 10 neurons are used for approximation. The results show that the network is useful as ail analyzer of such systems in experimental applications. The neural networks are validated for reduced test data with unknown faults.