Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.637992
Title: A wavelet-fuzzy based algorithm for condition monitoring and fault detection of a voltage source inverter
Author: Mamat-Ibrahim, M. R.
Awarding Body: University of Wales Swansea
Current Institution: Swansea University
Date of Award: 2003
Availability of Full Text:
Access through EThOS:
Abstract:
The popularity of the variable-speed induction machine as a drive mechanism has increased rapidly. This has led to the voltage source inverter induction machine being used to drive numerous applications such as electric vehicles and trains. Unfortunately, the condition monitoring and fault detection of these types of drives is an area, which has been left largely untouched by the research community. This is due to the high harmonic contents of the machine supply making the rigorous mathematical analysis of the drive complex. Fortunately, the interesting development in signal processing theory, especially wavelet transform, has sparked a new interest in condition monitoring of voltage source inverter induction machine. The wavelet transform have two important features, which, are important for the condition monitoring and fault detection purpose; time localization ability and multi-resolution analysis. Furthermore, the wavelet can be combined with an artificial intelligent system to provide an acceptable system with high accuracy and reliability. The work herein presented is a contribution to voltage source inverter induction machine condition monitoring and fault detection using the combination of wavelet transform and fuzzy logic. The research was concentrated on some typical fault events of voltage source inverter that allow reduced operating conditions of the drive system without triggering the short circuit protection.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.637992  DOI: Not available
Share: