Open AccessModel‐based exact technique to identify type and degree of eccentricity faults in induction motors
Author(s) -
Ojaghi Mansour,
Aghmasheh Reza,
Sabouri Mahdi
Publication year - 2016
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
ISSN - 1751-8679
DOI - 10.1049/iet-epa.2016.0026
Subject(s) - eccentricity (behavior) , fault (geology) , induction motor , control theory (sociology) , squirrel cage rotor , particle swarm optimization , degree (music) , type (biology) , computer science , control engineering , engineering , algorithm , physics , artificial intelligence , geology , paleontology , electrical engineering , control (management) , voltage , seismology , political science , acoustics , law
In spite of numerous research activities performed so far, determination of type and exact degree of the eccentricity faults in induction motors is challenging yet. This study presents a model‐based fault diagnosis technique for identifying all the three eccentricity fault types, including static, dynamic and mixed eccentricities, with their exact degrees in the mentioned motors. This technique uses a special analytic model prepared for simulating squirrel‐cage induction motors under healthy and all eccentricity fault conditions as well as the particle swarm optimisation method. Correct performance and effectiveness of the proposed technique is verified by using simulation and experiments. Finally, an algorithm is introduced for the eccentricity fault treatment using the identified degrees of the fault components and their time trends.