Stator inter-turn faults detection and localization using stator currents and concordia patterns - Neural network applications

Ibrahim F. El-Arabawy, Mahmoud I. Masoud, Abd El-Kader Mokhtari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

An inter-turn fault is one of the most difficult failures to detect Depending on the motor protection, the motor may continue to run but, soon or later, the heating in the short-circuited turns will cause severe failures. In this paper, the stator inter-turn faults are detected by observing the Concordia patterns and the behavior of the effective current values (RMS). These fault indicators have a specific behavior corresponding to each fault and can be used detect, locate and evaluate faults. Also two strategies are proposed to use multilayer feedforward neural networks (FFNN) in the fault detection, and both strategies are sketched and the best configuration is used. The network output can be interpreted, using a table, as a diagnosis report of the machine health. In addition, the use of two neural networks at the same time is proposed to improve the prediction accuracy.

Original languageEnglish
Title of host publication5th International Conference-Workshop Compatibility in Power Electronics, CPE 2007
DOIs
Publication statusPublished - 2007
Event5th International Conference-Workshop Compatibility in Power Electronics, CPE 2007 - Gdansk, Poland
Duration: May 29 2007Jun 1 2007

Other

Other5th International Conference-Workshop Compatibility in Power Electronics, CPE 2007
CountryPoland
CityGdansk
Period5/29/076/1/07

Keywords

  • Fault detection
  • Inter-turns
  • Neural networks
  • Park's current vector
  • RMS behavior

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Stator inter-turn faults detection and localization using stator currents and concordia patterns - Neural network applications'. Together they form a unique fingerprint.

  • Cite this

    El-Arabawy, I. F., Masoud, M. I., & El-Kader Mokhtari, A. (2007). Stator inter-turn faults detection and localization using stator currents and concordia patterns - Neural network applications. In 5th International Conference-Workshop Compatibility in Power Electronics, CPE 2007 [4296552] https://doi.org/10.1109/CPE.2007.4296552