A Damage Modes Extraction Method from AE Signal in Composite Laminates Based on DEEMD
An extraction method of damage modes in composite laminates from acoustic emission (AE) signal based on ensemble empirical mode decomposition (EEMD) and decorrelation algorithm is proposed. Based on previous works about damage modes identification of composite laminates using AE, the peak frequency...
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Veröffentlicht in: | Journal of nondestructive evaluation 2019-09, Vol.38 (3), p.1-10, Article 70 |
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description | An extraction method of damage modes in composite laminates from acoustic emission (AE) signal based on ensemble empirical mode decomposition (EEMD) and decorrelation algorithm is proposed. Based on previous works about damage modes identification of composite laminates using AE, the peak frequency of AE signal could distinguish various damage modes effectively. Energy generated by several damage modes can be included in a single AE signal, the empirical mode decomposition (EMD) could decompose AE signal into a set of intrinsic mode functions (IMFs), the peak frequency of each IMF was chosen to identify damage modes, but the analysis show that a single IMF would include components of dramatically disparate scales. Based on the above problems, the decorrelation ensemble empirical mode decomposition (DEEMD) method is put forward, DEEMD is the more effective solution for extracting all damage modes existing in a single AE signal than EMD, can eliminate mode mixing, would provide practical application guidance for composite laminates structure damage monitoring using AE. |
doi_str_mv | 10.1007/s10921-019-0609-2 |
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Based on previous works about damage modes identification of composite laminates using AE, the peak frequency of AE signal could distinguish various damage modes effectively. Energy generated by several damage modes can be included in a single AE signal, the empirical mode decomposition (EMD) could decompose AE signal into a set of intrinsic mode functions (IMFs), the peak frequency of each IMF was chosen to identify damage modes, but the analysis show that a single IMF would include components of dramatically disparate scales. Based on the above problems, the decorrelation ensemble empirical mode decomposition (DEEMD) method is put forward, DEEMD is the more effective solution for extracting all damage modes existing in a single AE signal than EMD, can eliminate mode mixing, would provide practical application guidance for composite laminates structure damage monitoring using AE.</description><identifier>ISSN: 0195-9298</identifier><identifier>EISSN: 1573-4862</identifier><identifier>DOI: 10.1007/s10921-019-0609-2</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Acoustic emission ; Algorithms ; Characterization and Evaluation of Materials ; Classical Mechanics ; Control ; Damage detection ; Decomposition ; Dynamical Systems ; Empirical analysis ; Engineering ; Laminates ; Peak frequency ; Solid Mechanics ; Structural damage ; Vibration</subject><ispartof>Journal of nondestructive evaluation, 2019-09, Vol.38 (3), p.1-10, Article 70</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2019</rights><rights>Copyright Springer Nature B.V. 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-a587696b358b87b4380f22b74854262aa1c3ab509ad3fcc5e386785b49bf572d3</citedby><cites>FETCH-LOGICAL-c353t-a587696b358b87b4380f22b74854262aa1c3ab509ad3fcc5e386785b49bf572d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10921-019-0609-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10921-019-0609-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Han, WenQin</creatorcontrib><creatorcontrib>Gu, AiJun</creatorcontrib><creatorcontrib>Zhou, Jinyu</creatorcontrib><title>A Damage Modes Extraction Method from AE Signal in Composite Laminates Based on DEEMD</title><title>Journal of nondestructive evaluation</title><addtitle>J Nondestruct Eval</addtitle><description>An extraction method of damage modes in composite laminates from acoustic emission (AE) signal based on ensemble empirical mode decomposition (EEMD) and decorrelation algorithm is proposed. Based on previous works about damage modes identification of composite laminates using AE, the peak frequency of AE signal could distinguish various damage modes effectively. Energy generated by several damage modes can be included in a single AE signal, the empirical mode decomposition (EMD) could decompose AE signal into a set of intrinsic mode functions (IMFs), the peak frequency of each IMF was chosen to identify damage modes, but the analysis show that a single IMF would include components of dramatically disparate scales. Based on the above problems, the decorrelation ensemble empirical mode decomposition (DEEMD) method is put forward, DEEMD is the more effective solution for extracting all damage modes existing in a single AE signal than EMD, can eliminate mode mixing, would provide practical application guidance for composite laminates structure damage monitoring using AE.</description><subject>Acoustic emission</subject><subject>Algorithms</subject><subject>Characterization and Evaluation of Materials</subject><subject>Classical Mechanics</subject><subject>Control</subject><subject>Damage detection</subject><subject>Decomposition</subject><subject>Dynamical Systems</subject><subject>Empirical analysis</subject><subject>Engineering</subject><subject>Laminates</subject><subject>Peak frequency</subject><subject>Solid Mechanics</subject><subject>Structural damage</subject><subject>Vibration</subject><issn>0195-9298</issn><issn>1573-4862</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp1kLFOwzAURS0EEqXwAWyWmA3PdhzbY2lTQGrFAJ0tJ3FKqiYudirB3-MqSExMb7j3XD0dhG4p3FMA-RApaEYJUE0gB03YGZpQITnJVM7O0SQFgmim1SW6inEHAFpJOkGbGV7Yzm4dXvvaRVx8DcFWQ-t7vHbDh69xE3yHZwV-a7e93eO2x3PfHXxsB4dXtmt7OyTu0UZX40QtimK9uEYXjd1Hd_N7p2izLN7nz2T1-vQyn61IxQUfiBVK5jovuVClkmXGFTSMlTJTImM5s5ZW3JYCtK15U1XCcZVLJcpMl42QrOZTdDfuHoL_PLo4mJ0_hvRmNIwJnQEDTVOLjq0q-BiDa8whtJ0N34aCOdkzoz2TJJmTPcMSw0Ympm6_deFv-X_oB5C4b1Q</recordid><startdate>20190901</startdate><enddate>20190901</enddate><creator>Han, WenQin</creator><creator>Gu, AiJun</creator><creator>Zhou, Jinyu</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20190901</creationdate><title>A Damage Modes Extraction Method from AE Signal in Composite Laminates Based on DEEMD</title><author>Han, WenQin ; Gu, AiJun ; Zhou, Jinyu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-a587696b358b87b4380f22b74854262aa1c3ab509ad3fcc5e386785b49bf572d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Acoustic emission</topic><topic>Algorithms</topic><topic>Characterization and Evaluation of Materials</topic><topic>Classical Mechanics</topic><topic>Control</topic><topic>Damage detection</topic><topic>Decomposition</topic><topic>Dynamical Systems</topic><topic>Empirical analysis</topic><topic>Engineering</topic><topic>Laminates</topic><topic>Peak frequency</topic><topic>Solid Mechanics</topic><topic>Structural damage</topic><topic>Vibration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Han, WenQin</creatorcontrib><creatorcontrib>Gu, AiJun</creatorcontrib><creatorcontrib>Zhou, Jinyu</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of nondestructive evaluation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Han, WenQin</au><au>Gu, AiJun</au><au>Zhou, Jinyu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Damage Modes Extraction Method from AE Signal in Composite Laminates Based on DEEMD</atitle><jtitle>Journal of nondestructive evaluation</jtitle><stitle>J Nondestruct Eval</stitle><date>2019-09-01</date><risdate>2019</risdate><volume>38</volume><issue>3</issue><spage>1</spage><epage>10</epage><pages>1-10</pages><artnum>70</artnum><issn>0195-9298</issn><eissn>1573-4862</eissn><abstract>An extraction method of damage modes in composite laminates from acoustic emission (AE) signal based on ensemble empirical mode decomposition (EEMD) and decorrelation algorithm is proposed. Based on previous works about damage modes identification of composite laminates using AE, the peak frequency of AE signal could distinguish various damage modes effectively. Energy generated by several damage modes can be included in a single AE signal, the empirical mode decomposition (EMD) could decompose AE signal into a set of intrinsic mode functions (IMFs), the peak frequency of each IMF was chosen to identify damage modes, but the analysis show that a single IMF would include components of dramatically disparate scales. Based on the above problems, the decorrelation ensemble empirical mode decomposition (DEEMD) method is put forward, DEEMD is the more effective solution for extracting all damage modes existing in a single AE signal than EMD, can eliminate mode mixing, would provide practical application guidance for composite laminates structure damage monitoring using AE.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10921-019-0609-2</doi><tpages>10</tpages></addata></record> |
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subjects | Acoustic emission Algorithms Characterization and Evaluation of Materials Classical Mechanics Control Damage detection Decomposition Dynamical Systems Empirical analysis Engineering Laminates Peak frequency Solid Mechanics Structural damage Vibration |
title | A Damage Modes Extraction Method from AE Signal in Composite Laminates Based on DEEMD |
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