Integrated Fault Evaluation Through Fusion Algorithm Supported by Kalman Filter

Mousavi S., Bayram Kara D., Şeker Ş. S.

TRAITEMENT DU SIGNAL, cilt.37, sa.6, ss.975-987, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 6
  • Basım Tarihi: 2020
  • Doi Numarası: 10.18280/ts.370610
  • Dergi Adı: TRAITEMENT DU SIGNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Business Source Elite, Business Source Premier, Compendex, zbMATH
  • Sayfa Sayıları: ss.975-987
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

An Integrated Fault Evaluation (IFE) process is proposed in this study. It includes Sensor Validation (SV), Fault Detection (FD) and Fault Source Identification (FSI). The proposed algorithm employs data fusion algorithm enhanced by Kalman filter (KF). As the case study, vibration signals representing different aging states of an induction motor are used. The vibration data collected from two identical sensors with different measurement and process noises are achieved. Through the statistical and frequency domain characteristics, IFE is realized. The most prominent contribution of the study is the capability of distinction between the aging of the system and the process problems. For this aim, a rate representing the healthiness, which can discern the impact of the process noise and system aging, is calculated.