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Blind source separation based vibration mode identification
In this paper, a novel method for linear normal mode (LNM) identification based on blind source separation (BSS) is introduced. Modal coordinates are considered as a specific case of sources that have certain time structure. This structure makes modal coordinates identifiable by many BSS algorithms....
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| Published in: | Mechanical systems and signal processing 2007-11, Vol.21 (8), p.3072-3087 |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
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| cited_by | cdi_FETCH-LOGICAL-c430t-894df6e8cc306cbafcc6ca9bc7b5e6b12440c1e6db53d481560ac5be533b0a363 |
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| cites | cdi_FETCH-LOGICAL-c430t-894df6e8cc306cbafcc6ca9bc7b5e6b12440c1e6db53d481560ac5be533b0a363 |
| container_end_page | 3087 |
| container_issue | 8 |
| container_start_page | 3072 |
| container_title | Mechanical systems and signal processing |
| container_volume | 21 |
| creator | Zhou, Wenliang Chelidze, David |
| description | In this paper, a novel method for
linear normal mode (LNM) identification based on
blind source separation (BSS) is introduced. Modal coordinates are considered as a specific case of sources that have certain time structure. This structure makes modal coordinates identifiable by many BSS algorithms. However, algorithms based on second-order statistics are particularly suited for extracting LNMs of a vibration system. Two well-known BSS algorithms are considered. First,
algorithm for multiple unknown signals extraction (AMUSE) is used to illustrate the similarity with
Ibrahim time domain (ITD) modal identification method. Second,
second order blind identification (SOBI) is used to demonstrate noise robustness of BSS-based mode shape extraction. Numerical simulations and experimental results from these BSS algorithms and ITD method are presented. |
| doi_str_mv | 10.1016/j.ymssp.2007.05.007 |
| format | article |
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linear normal mode (LNM) identification based on
blind source separation (BSS) is introduced. Modal coordinates are considered as a specific case of sources that have certain time structure. This structure makes modal coordinates identifiable by many BSS algorithms. However, algorithms based on second-order statistics are particularly suited for extracting LNMs of a vibration system. Two well-known BSS algorithms are considered. First,
algorithm for multiple unknown signals extraction (AMUSE) is used to illustrate the similarity with
Ibrahim time domain (ITD) modal identification method. Second,
second order blind identification (SOBI) is used to demonstrate noise robustness of BSS-based mode shape extraction. Numerical simulations and experimental results from these BSS algorithms and ITD method are presented.</description><identifier>ISSN: 0888-3270</identifier><identifier>EISSN: 1096-1216</identifier><identifier>DOI: 10.1016/j.ymssp.2007.05.007</identifier><language>eng</language><publisher>London: Elsevier Ltd</publisher><subject>Blind source separation ; Exact sciences and technology ; Fundamental areas of phenomenology (including applications) ; Independent component analysis ; Measurement and testing methods ; Modal analysis ; Physics ; Solid mechanics ; Structural and continuum mechanics ; Vibration tests ; Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...)</subject><ispartof>Mechanical systems and signal processing, 2007-11, Vol.21 (8), p.3072-3087</ispartof><rights>2007 Elsevier Ltd</rights><rights>2008 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c430t-894df6e8cc306cbafcc6ca9bc7b5e6b12440c1e6db53d481560ac5be533b0a363</citedby><cites>FETCH-LOGICAL-c430t-894df6e8cc306cbafcc6ca9bc7b5e6b12440c1e6db53d481560ac5be533b0a363</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=19681571$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhou, Wenliang</creatorcontrib><creatorcontrib>Chelidze, David</creatorcontrib><title>Blind source separation based vibration mode identification</title><title>Mechanical systems and signal processing</title><description>In this paper, a novel method for
linear normal mode (LNM) identification based on
blind source separation (BSS) is introduced. Modal coordinates are considered as a specific case of sources that have certain time structure. This structure makes modal coordinates identifiable by many BSS algorithms. However, algorithms based on second-order statistics are particularly suited for extracting LNMs of a vibration system. Two well-known BSS algorithms are considered. First,
algorithm for multiple unknown signals extraction (AMUSE) is used to illustrate the similarity with
Ibrahim time domain (ITD) modal identification method. Second,
second order blind identification (SOBI) is used to demonstrate noise robustness of BSS-based mode shape extraction. Numerical simulations and experimental results from these BSS algorithms and ITD method are presented.</description><subject>Blind source separation</subject><subject>Exact sciences and technology</subject><subject>Fundamental areas of phenomenology (including applications)</subject><subject>Independent component analysis</subject><subject>Measurement and testing methods</subject><subject>Modal analysis</subject><subject>Physics</subject><subject>Solid mechanics</subject><subject>Structural and continuum mechanics</subject><subject>Vibration tests</subject><subject>Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...)</subject><issn>0888-3270</issn><issn>1096-1216</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNp9UE1LxDAQDaLguvoLvPSit9ZJ06Yt4kEXv2DBi55DMplCln6sSXfBf2_2A7x5eszw3pt5j7FrDhkHLu9W2U8fwjrLAaoMyizCCZtxaGTKcy5P2Qzquk5FXsE5uwhhBQBNAXLG7p86N9gkjBuPlARaa68nNw6J0YFssnXmOPejpcRZGibXOtzvLtlZq7tAV0ecs6-X58_FW7r8eH1fPC5TLARMad0UtpVUIwqQaHSLKFE3BitTkjQ8LwpATtKaUtii5qUEjaWhUggDWkgxZ7cH37UfvzcUJtW7gNR1eqBxE5SIWfK6riJRHIjoxxA8tWrtXa_9j-KgdkWpldoXpXZFKShVhKi6OdrrgLprvR7QhT9pI-NPFY-8hwOPYtatI68COhqQrPOEk7Kj-_fOL2xIgLI</recordid><startdate>20071101</startdate><enddate>20071101</enddate><creator>Zhou, Wenliang</creator><creator>Chelidze, David</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20071101</creationdate><title>Blind source separation based vibration mode identification</title><author>Zhou, Wenliang ; Chelidze, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c430t-894df6e8cc306cbafcc6ca9bc7b5e6b12440c1e6db53d481560ac5be533b0a363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Blind source separation</topic><topic>Exact sciences and technology</topic><topic>Fundamental areas of phenomenology (including applications)</topic><topic>Independent component analysis</topic><topic>Measurement and testing methods</topic><topic>Modal analysis</topic><topic>Physics</topic><topic>Solid mechanics</topic><topic>Structural and continuum mechanics</topic><topic>Vibration tests</topic><topic>Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhou, Wenliang</creatorcontrib><creatorcontrib>Chelidze, David</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering 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>Mechanical systems and signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhou, Wenliang</au><au>Chelidze, David</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Blind source separation based vibration mode identification</atitle><jtitle>Mechanical systems and signal processing</jtitle><date>2007-11-01</date><risdate>2007</risdate><volume>21</volume><issue>8</issue><spage>3072</spage><epage>3087</epage><pages>3072-3087</pages><issn>0888-3270</issn><eissn>1096-1216</eissn><abstract>In this paper, a novel method for
linear normal mode (LNM) identification based on
blind source separation (BSS) is introduced. Modal coordinates are considered as a specific case of sources that have certain time structure. This structure makes modal coordinates identifiable by many BSS algorithms. However, algorithms based on second-order statistics are particularly suited for extracting LNMs of a vibration system. Two well-known BSS algorithms are considered. First,
algorithm for multiple unknown signals extraction (AMUSE) is used to illustrate the similarity with
Ibrahim time domain (ITD) modal identification method. Second,
second order blind identification (SOBI) is used to demonstrate noise robustness of BSS-based mode shape extraction. Numerical simulations and experimental results from these BSS algorithms and ITD method are presented.</abstract><cop>London</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ymssp.2007.05.007</doi><tpages>16</tpages></addata></record> |
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| ispartof | Mechanical systems and signal processing, 2007-11, Vol.21 (8), p.3072-3087 |
| issn | 0888-3270 1096-1216 |
| language | eng |
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| source | ScienceDirect Journals |
| subjects | Blind source separation Exact sciences and technology Fundamental areas of phenomenology (including applications) Independent component analysis Measurement and testing methods Modal analysis Physics Solid mechanics Structural and continuum mechanics Vibration tests Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...) |
| title | Blind source separation based vibration mode identification |
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