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Induction Motor Bearing Fault Analysis Using a Root-MUSIC Method
This paper describes a new diagnosis approach, the Root-Multiple Signal Classification (MUSIC) (RM) method, for identification of the progressive cracking in the bearing of induction motors. This approach has several advantages compared with the stator current spectral analysis using the conventiona...
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Published in: | IEEE transactions on industry applications 2016-09, Vol.52 (5), p.3851-3860 |
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creator | Boudinar, Ahmed Hamida Benouzza, Noureddine Bendiabdellah, Azeddine Khodja, Mohammed-El-Amine |
description | This paper describes a new diagnosis approach, the Root-Multiple Signal Classification (MUSIC) (RM) method, for identification of the progressive cracking in the bearing of induction motors. This approach has several advantages compared with the stator current spectral analysis using the conventional Periodogram method. Indeed, the main advantage of this approach is its very good frequency resolution for a very short acquisition time, something impossible to achieve with the conventional method. However, in order to reduce the computation time, which is the main drawback of the RM method, this method will be applied to only a specified frequency band; one that carries information about the sought fault. Experimental results show the effectiveness of the RM method on the reliability of the incipient bearing fault detection. |
doi_str_mv | 10.1109/TIA.2016.2581143 |
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This approach has several advantages compared with the stator current spectral analysis using the conventional Periodogram method. Indeed, the main advantage of this approach is its very good frequency resolution for a very short acquisition time, something impossible to achieve with the conventional method. However, in order to reduce the computation time, which is the main drawback of the RM method, this method will be applied to only a specified frequency band; one that carries information about the sought fault. Experimental results show the effectiveness of the RM method on the reliability of the incipient bearing fault detection.</description><identifier>ISSN: 0093-9994</identifier><identifier>EISSN: 1939-9367</identifier><identifier>DOI: 10.1109/TIA.2016.2581143</identifier><identifier>CODEN: ITIACR</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Bearing ; cracks ; Fault diagnosis ; frequency band ; Harmonic analysis ; induction motor ; Induction motors ; Matrix decomposition ; power spectral density (PSD) ; Root-Multiple Signal Classification (MUSIC) ; Signal resolution ; spectral analysis ; stator current ; Stators ; Time-frequency analysis</subject><ispartof>IEEE transactions on industry applications, 2016-09, Vol.52 (5), p.3851-3860</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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This approach has several advantages compared with the stator current spectral analysis using the conventional Periodogram method. Indeed, the main advantage of this approach is its very good frequency resolution for a very short acquisition time, something impossible to achieve with the conventional method. However, in order to reduce the computation time, which is the main drawback of the RM method, this method will be applied to only a specified frequency band; one that carries information about the sought fault. Experimental results show the effectiveness of the RM method on the reliability of the incipient bearing fault detection.</description><subject>Bearing</subject><subject>cracks</subject><subject>Fault diagnosis</subject><subject>frequency band</subject><subject>Harmonic analysis</subject><subject>induction motor</subject><subject>Induction motors</subject><subject>Matrix decomposition</subject><subject>power spectral density (PSD)</subject><subject>Root-Multiple Signal Classification (MUSIC)</subject><subject>Signal resolution</subject><subject>spectral analysis</subject><subject>stator current</subject><subject>Stators</subject><subject>Time-frequency analysis</subject><issn>0093-9994</issn><issn>1939-9367</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNo9kM9Lw0AQhRdRsFbvgpeA59SZ3c0mc7OWVgMtgrbnJT92NaVm625y6H9vSoungcf3HsPH2D3CBBHoaZ1PJxxQTXiSIUpxwUZIgmISKr1kIwASMRHJa3YTwhYAZYJyxJ7ztu6rrnFttHKd89GLKXzTfkWLot910bQtdofQhGgTjmERfTjXxavNZz6LVqb7dvUtu7LFLpi78x2zzWK-nr3Fy_fXfDZdxhUn7GKq08yiKMuyVhIQRcUhSS1Ya2tMVFZWyIVQtqBKGglclRJSQyLh0oJUqRizx9Pu3rvf3oROb13vh_eCxkwAKVKZGig4UZV3IXhj9d43P4U_aAR99KQHT_roSZ89DZWHU6UxxvzjqSQ-EOIPV0hhLQ</recordid><startdate>201609</startdate><enddate>201609</enddate><creator>Boudinar, Ahmed Hamida</creator><creator>Benouzza, Noureddine</creator><creator>Bendiabdellah, Azeddine</creator><creator>Khodja, Mohammed-El-Amine</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>201609</creationdate><title>Induction Motor Bearing Fault Analysis Using a Root-MUSIC Method</title><author>Boudinar, Ahmed Hamida ; Benouzza, Noureddine ; Bendiabdellah, Azeddine ; Khodja, Mohammed-El-Amine</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-9d78f13bbbd640113c2057f0fffd1568bc12336fa9c4e4026b407e93524f04673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Bearing</topic><topic>cracks</topic><topic>Fault diagnosis</topic><topic>frequency band</topic><topic>Harmonic analysis</topic><topic>induction motor</topic><topic>Induction motors</topic><topic>Matrix decomposition</topic><topic>power spectral density (PSD)</topic><topic>Root-Multiple Signal Classification (MUSIC)</topic><topic>Signal resolution</topic><topic>spectral analysis</topic><topic>stator current</topic><topic>Stators</topic><topic>Time-frequency analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Boudinar, Ahmed Hamida</creatorcontrib><creatorcontrib>Benouzza, Noureddine</creatorcontrib><creatorcontrib>Bendiabdellah, Azeddine</creatorcontrib><creatorcontrib>Khodja, Mohammed-El-Amine</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library Online</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on industry applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Boudinar, Ahmed Hamida</au><au>Benouzza, Noureddine</au><au>Bendiabdellah, Azeddine</au><au>Khodja, Mohammed-El-Amine</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Induction Motor Bearing Fault Analysis Using a Root-MUSIC Method</atitle><jtitle>IEEE transactions on industry applications</jtitle><stitle>TIA</stitle><date>2016-09</date><risdate>2016</risdate><volume>52</volume><issue>5</issue><spage>3851</spage><epage>3860</epage><pages>3851-3860</pages><issn>0093-9994</issn><eissn>1939-9367</eissn><coden>ITIACR</coden><abstract>This paper describes a new diagnosis approach, the Root-Multiple Signal Classification (MUSIC) (RM) method, for identification of the progressive cracking in the bearing of induction motors. This approach has several advantages compared with the stator current spectral analysis using the conventional Periodogram method. Indeed, the main advantage of this approach is its very good frequency resolution for a very short acquisition time, something impossible to achieve with the conventional method. However, in order to reduce the computation time, which is the main drawback of the RM method, this method will be applied to only a specified frequency band; one that carries information about the sought fault. Experimental results show the effectiveness of the RM method on the reliability of the incipient bearing fault detection.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIA.2016.2581143</doi><tpages>10</tpages></addata></record> |
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subjects | Bearing cracks Fault diagnosis frequency band Harmonic analysis induction motor Induction motors Matrix decomposition power spectral density (PSD) Root-Multiple Signal Classification (MUSIC) Signal resolution spectral analysis stator current Stators Time-frequency analysis |
title | Induction Motor Bearing Fault Analysis Using a Root-MUSIC Method |
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