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, ss.813-823, 2015 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 23 Konu: 3
  • Basım Tarihi: 2015
  • Doi Numarası: 10.3906/elk-1210-58
  • Dergi Adı: TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
  • Sayfa Sayıları: ss.813-823

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.