Use of a combined SVD-Kalman filter approach for induction motor broken rotor bars identification

Abstract This paper describes a new parametric spectral estimator for the identification of rotor bar fault of an induction motor by analyzing the stator current. This approach combines two methods: The first one, the Singular Value Decomposition method which allows the accurate detection and locati...

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Hauptverfasser: K. Azouzi, A. H. Boudinar, F. A. Aimer, A. Bendiabdellah
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A. H. Boudinar
F. A. Aimer
A. Bendiabdellah
description Abstract This paper describes a new parametric spectral estimator for the identification of rotor bar fault of an induction motor by analyzing the stator current. This approach combines two methods: The first one, the Singular Value Decomposition method which allows the accurate detection and location of the fault's signature frequency. The second method allows the estimation of the fault amplitude. To this end, the Kalman filter is used for its efficient estimation of both amplitude and phase using the frequencies obtained by the first method. This combination of both methods gives a better frequency resolution for a very short acquisition time, which cannot be obtained using the conventional method of the Periodogram. Moreover, in order to reduce the significant computation time resulting from the use of the Kalman filter, the proposed approach is applied only to the frequency band where the fault signature is likely to appear. A series of tests will be carried out on real signals representing rotor faults.
doi_str_mv 10.6084/m9.figshare.6235274
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Azouzi ; A. H. Boudinar ; F. A. Aimer ; A. Bendiabdellah</creator><creatorcontrib>K. Azouzi ; A. H. Boudinar ; F. A. Aimer ; A. Bendiabdellah</creatorcontrib><description>Abstract This paper describes a new parametric spectral estimator for the identification of rotor bar fault of an induction motor by analyzing the stator current. This approach combines two methods: The first one, the Singular Value Decomposition method which allows the accurate detection and location of the fault's signature frequency. The second method allows the estimation of the fault amplitude. To this end, the Kalman filter is used for its efficient estimation of both amplitude and phase using the frequencies obtained by the first method. This combination of both methods gives a better frequency resolution for a very short acquisition time, which cannot be obtained using the conventional method of the Periodogram. Moreover, in order to reduce the significant computation time resulting from the use of the Kalman filter, the proposed approach is applied only to the frequency band where the fault signature is likely to appear. 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Moreover, in order to reduce the significant computation time resulting from the use of the Kalman filter, the proposed approach is applied only to the frequency band where the fault signature is likely to appear. 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Bendiabdellah</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>K. Azouzi</au><au>A. H. Boudinar</au><au>F. A. Aimer</au><au>A. Bendiabdellah</au><format>book</format><genre>unknown</genre><ristype>DATA</ristype><title>Use of a combined SVD-Kalman filter approach for induction motor broken rotor bars identification</title><date>2018-05-09</date><risdate>2018</risdate><abstract>Abstract This paper describes a new parametric spectral estimator for the identification of rotor bar fault of an induction motor by analyzing the stator current. This approach combines two methods: The first one, the Singular Value Decomposition method which allows the accurate detection and location of the fault's signature frequency. The second method allows the estimation of the fault amplitude. 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FOS: Other engineering and technologies
FOS: Physical sciences
Optical Physics not elsewhere classified
title Use of a combined SVD-Kalman filter approach for induction motor broken rotor bars identification
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