Detection of bearing defects in three-phase induction motors using Park's transform and radial basis function neural networks

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Onel I. Y., Dalci K. B., Senol I., ÖNEL İ. Y.

SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, cilt.31, ss.235-244, 2006 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 31
  • Basım Tarihi: 2006
  • Doi Numarası: 10.1007/bf02703379
  • Dergi Adı: SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.235-244
  • Anahtar Kelimeler: induction motor, stator current, bearing damage, Park's transform, RBF neural network, STATOR CURRENT, FAULT-DETECTION
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

This paper investigates the application of induction motor stator current si-nature analysis (MCSA) using; Park's transform for the detection of rolling element bearing damages in three-phase induction motor. The paper first discusses bearing faults and Park's transform, and then gives a brief overview of the radial basis function (RBF) neural networks algorithm. Finally, system information and the experimental results are presented. Data acquisition and Park's transform algorithm are achieved by using LabVIEW and the neural network algorithm is achieved by using MATLAB programming language. Experimental results show that it is possible to detect bearing damage in induction motors using an ANN algorithm.