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https://hdl.handle.net/2440/81386
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Type: | Conference paper |
Title: | Induction motor stator faults diagnosis by using parameter estimation algorithms |
Author: | Duan, F. Zivanovic, R. |
Citation: | Proceedings 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED), Escuela Técnica Superior de Ingenieros Industriales Universitat Politecnica de Valencia Valencia, Spain, August 27-30, 2013: pp.274-280 |
Publisher: | IEEE |
Publisher Place: | USB |
Issue Date: | 2013 |
ISBN: | 9781479900237 |
Conference Name: | IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (9th : 2013 : Valencia, Spain) |
Statement of Responsibility: | Fang Duan, Rastko Zivanovic |
Abstract: | Parameter estimation is a cost-effective method for fault detection of induction motors. This method is based on detecting change of the characteristic parameters at presence of fault. However, the challenge of parameter estimation is nonlinearity of a machine model which results in multiple local minima involved during the computation process. This paper investigates the suitability of local and global search methods to be used in the estimation of characteristic parameters that are indicating stator short circuit faults. Results of practical case studies are presented where two search methods (local and global) are evaluated and compared. A further study in noisy environment proves the feasibility of diagnosing the fault based on stator currents with low signal to noise ratio. © 2013 IEEE. |
Rights: | ©2013 IEEE |
DOI: | 10.1109/DEMPED.2013.6645728 |
Published version: | http://dx.doi.org/10.1109/demped.2013.6645728 |
Appears in Collections: | Aurora harvest Electrical and Electronic Engineering publications |
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