Induction Motor Identification from Acoustic Noise Spectrum by a Covariance Subspace Algorithm

AKÇAY H., GERMEN E., TÜRKAY S.

14th IEEE International Conference on Control and Automation (ICCA), Alaska, Amerika Birleşik Devletleri, 12 - 15 Haziran 2018, ss.957-962 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/icca.2018.8444181
  • Basıldığı Şehir: Alaska
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.957-962
  • Anahtar Kelimeler: system identification, power spectrum, covariance subspace algorithm, fault detection, induction motor, VIBRATION
  • Anadolu Üniversitesi Adresli: Evet

Özet

In this paper, we study identification of induction motors by using a recently developed covariance-based subspace algorithm from sound measurements. The sound data are collected by an array of five-microphones placed hemispherically around motors in a reverberant and noisy room. It is demonstrated that mechanical faults, frequently encountered in induction motors, are isolated by the proposed identification algorithm. The estimated acoustic noise spectra can be utilized in the development of preventive maintenance programs for induction motors in service.