Parameter Estimation for Electric Motor Condition Monitoring

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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

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Official URL: http://tvi-in.com/news_view.asp?id=692

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:	Author Author Publisher
Depositing User:	Sara Taylor
Date Deposited:	24 Apr 2012 16:12
Last Modified:	24 Apr 2012 16:13
URI:	http://eprints.hud.ac.uk/id/eprint/13352

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