Search:
Computing and Library Services - delivering an inspiring information environment

Parameter Estimation for Electric Motor Condition Monitoring

Treetrong, Juggrapong, Sinha, Jyoti K., Gu, Fengshou and Ball, Andrew (2012) Parameter Estimation for Electric Motor Condition Monitoring. Advances in Vibration Engineering, 11 (1). pp. 75-84. ISSN 0972-5768

Metadata only available from this repository.

Abstract

This paper presents parameter identification technique to quantify the faults in motor condition monitoring. Genetic Algorithm (GA) has been used as a key technique to estimate the motor parameters. The zero-sequence voltage equation for the stator has been used as a model to estimate motor stator parameters – the stator resistance and the stator leakage inductance. The comparison of the parameter estimation by the earlier Recursive Least Square (RLS) method and the proposed GA technique has been discussed. The GA technique shows better accuracy in the estimation. The estimation has been tested on both simulations and a real test motor.

Item Type: Article
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
Related URLs:
Depositing User: Sara Taylor
Date Deposited: 24 Apr 2012 16:12
Last Modified: 04 Jun 2013 12:29
URI: http://eprints.hud.ac.uk/id/eprint/13352

Item control for Repository Staff only:

View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©