Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.498681
Title: The use of parameter identification methods for the condition monitoring of electric motor drives
Author: Treetrong, Juggrapong
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2009
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Abstract:
Induction motors are the most widely used motors among electric motors in industries. These are due to their reasonable cost, reasonably small sizes, ruggedness, low maintenance, and operation with an easily available power supply including their high reliability. However, these motors are often exposed to hostile environments during operation. These abnormal situations may lead to early deterioration of motors i.e., development of faults. Without any actions, these faults may increase to severe problems such as secondary damages to downstream equipment, unexpected breakdowns. Condition monitoring is modern technologies generally used to observe the health of electric machines regularly. Several condition monitoring methods for the induction motors have been developed using the MCSA (Motor Current Signature Analysis) and vibration analysis which explore the possibility of the early detection of developing faults in the electric machines so that the rectification can be planned in advance before any catastrophic failure. Vibration based condition monitoring requires the installation of number of vibration sensors and can detect the early fault but the quantification of the electrical faults (either in the stator or rotor or both) is generally impossible. However the other option - the MCSA doesn't require additional sensors. Hence the present research study utilized the use of the MCSA for the early detection and the quantification of faults which would be useful for quick rectification of the identified faults in practice.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.498681  DOI: Not available
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