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Title: Analysis and simulation of faults in squirrel cage motors
Author: Stavrou, Andreas
ISNI:       0000 0001 3478 4630
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 1994
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Condition based maintenance of electrical machines offers significant advantages for industry. A large part of the research effort in this area is directed towards the evaluation of fault conditions. This thesis is concerned with analysing and modelling faults in induction motors. A method for evaluating the performance of induction machines with static and dynamic eccentricity is developed, using harmonic analysis of the air gap permeance. Models able to simulate eccentricity are presented. The slip ring model equations are obtained and then used to obtain the commutator models transformed to a single reference frame. A variety of effects accompanying these fault conditions are analysed, for example variation of the eccentricity level due to unbalanced magnetic pull and the possibilities of additional vibration harmonics examined. Damping of eccentricity fields due to current redistribution, saturation and slotting are discussed. Some general steady state calculations are also presented which show that the performance of the machine need not be changed over the operating range, due to such a fault. The characteristics of combined static and dynamic eccentricity are examined and it is shown that the combined asymmetry generates additional harmonic components which are not related to those which occur when the two asymmetries take place in isolation. The development of a simulation model of machines with broken rotor bars, based on the variation in rotor parameters is presented. Experimental investigations focus mainly on observable differences in the torque transient characteristics, due to such a condition. The possibilities for using current monitoring to identify inter-turn short circuits are investigated.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Induction machines