Mechanical fault detection in permanent magnet synchronous motors using equal width discretization-based probability distribution and a neural network model

Akar M., Hekim M., ORHAN U.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, cilt.23, sa.3, ss.813-823, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 23 Sayı: 3
  • Basım Tarihi: 2015
  • Doi Numarası: 10.3906/elk-1210-58
  • Dergi Adı: TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.813-823
  • Anahtar Kelimeler: Permanent magnet synchronous motor (PMSM), eccentricity, bearing faults, equal width discretization (EWD), probability distribution, artificial neural network, ECCENTRICITY
  • Çukurova Üniversitesi Adresli: Evet

Özet

This paper focuses on detecting the static eccentricity and bearing faults of a permanent magnet synchronous motor (PMSM) using probability distributions based on equal width discretization (EWD) and a multilayer perceptron neural network (MLPNN) model. In order to achieve this, the PMSM stator current values were measured in the cases of healthy, static eccentricity, and bearing faults for the conditions of three speeds and five loads. The data was discretized into several ranges through the EWD method, the probability distributions were computed according to the number of current values belonging to each range, and these distributions were then used as inputs to the MLPNN model.