Integrated Fault Evaluation Through Fusion Algorithm Supported by Kalman Filter

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

TRAITEMENT DU SIGNAL, vol.37, no.6, pp.975-987, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 6
  • Publication Date: 2020
  • Doi Number: 10.18280/ts.370610
  • Journal Name: TRAITEMENT DU SIGNAL
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Business Source Elite, Business Source Premier, Compendex, zbMATH
  • Page Numbers: pp.975-987
  • Istanbul Technical University Affiliated: Yes

Abstract

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.