Defect distribution and reliability assessment of wind turbine blades
In this paper, two stochastic models for the distribution of defects in wind turbine blades are proposed. The first model assumes that the individual defects are completely randomly distributed in the blade. The second model assumes that the defects occur in clusters of different size, based on the...
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| Veröffentlicht in: | Engineering structures 2011, Vol.33 (1), p.171-180 |
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| creator | Toft, Henrik Stensgaard Branner, Kim Berring, Peter Sørensen, John Dalsgaard |
| description | In this paper, two stochastic models for the distribution of defects in wind turbine blades are proposed. The first model assumes that the individual defects are completely randomly distributed in the blade. The second model assumes that the defects occur in clusters of different size, based on the assumption that one error in the production process tends to trigger several defects. For both models, additional information, such as number, type, and size of the defects, is included as stochastic variables.
In a numerical example, the reliability is estimated for a generic wind turbine blade model both with and without defects in terms of delaminations. The reliability of the blade decreases when defects are included. However, the distribution of the defects influences how much the reliability is decreased. It is also shown how non-destructive inspection (NDI) after production can be used to update the reliability for the wind turbine blade using Bayesian statistics. |
| doi_str_mv | 10.1016/j.engstruct.2010.10.002 |
| format | Article |
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In a numerical example, the reliability is estimated for a generic wind turbine blade model both with and without defects in terms of delaminations. The reliability of the blade decreases when defects are included. However, the distribution of the defects influences how much the reliability is decreased. It is also shown how non-destructive inspection (NDI) after production can be used to update the reliability for the wind turbine blade using Bayesian statistics.</description><identifier>ISSN: 0141-0296</identifier><identifier>EISSN: 1873-7323</identifier><identifier>DOI: 10.1016/j.engstruct.2010.10.002</identifier><identifier>CODEN: ENSTDF</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Applied sciences ; Building failures (cracks, physical changes, etc.) ; Buildings. Public works ; Computation methods. Tables. Charts ; Defects ; Delamination ; Durability. Pathology. Repairing. Maintenance ; Energy ; Exact sciences and technology ; Natural energy ; Probabilistic methods ; Reliability ; Structural analysis. Stresses ; System effects ; Wind energy ; Wind turbine blades</subject><ispartof>Engineering structures, 2011, Vol.33 (1), p.171-180</ispartof><rights>2010 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c377t-5cb5693ebc48b52f26be3fa52871e6d8fd4e20375ff80f59ce3e2c7c9236859e3</citedby><cites>FETCH-LOGICAL-c377t-5cb5693ebc48b52f26be3fa52871e6d8fd4e20375ff80f59ce3e2c7c9236859e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.engstruct.2010.10.002$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>315,781,785,3551,4025,27928,27929,27930,46000</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23630727$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Toft, Henrik Stensgaard</creatorcontrib><creatorcontrib>Branner, Kim</creatorcontrib><creatorcontrib>Berring, Peter</creatorcontrib><creatorcontrib>Sørensen, John Dalsgaard</creatorcontrib><title>Defect distribution and reliability assessment of wind turbine blades</title><title>Engineering structures</title><description>In this paper, two stochastic models for the distribution of defects in wind turbine blades are proposed. The first model assumes that the individual defects are completely randomly distributed in the blade. The second model assumes that the defects occur in clusters of different size, based on the assumption that one error in the production process tends to trigger several defects. For both models, additional information, such as number, type, and size of the defects, is included as stochastic variables.
In a numerical example, the reliability is estimated for a generic wind turbine blade model both with and without defects in terms of delaminations. The reliability of the blade decreases when defects are included. However, the distribution of the defects influences how much the reliability is decreased. It is also shown how non-destructive inspection (NDI) after production can be used to update the reliability for the wind turbine blade using Bayesian statistics.</description><subject>Applied sciences</subject><subject>Building failures (cracks, physical changes, etc.)</subject><subject>Buildings. Public works</subject><subject>Computation methods. Tables. Charts</subject><subject>Defects</subject><subject>Delamination</subject><subject>Durability. Pathology. Repairing. Maintenance</subject><subject>Energy</subject><subject>Exact sciences and technology</subject><subject>Natural energy</subject><subject>Probabilistic methods</subject><subject>Reliability</subject><subject>Structural analysis. Stresses</subject><subject>System effects</subject><subject>Wind energy</subject><subject>Wind turbine blades</subject><issn>0141-0296</issn><issn>1873-7323</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqFkMlOwzAQQC0EEqXwDeSCOKV4qWPnWJWySJW4wNlynDFylSbF44D697gUceU00syb7RFyzeiMUVbdbWbQv2OKo0szTn-yM0r5CZkwrUSpBBenZELZnJWU19U5uUDc0ExoTSdkdQ8eXCrakEeEZkxh6Avbt0WELtgmdCHtC4sIiFvoUzH44ivkchpjE3ooms62gJfkzNsO4eo3Tsnbw-p1-VSuXx6fl4t16YRSqZSukVUtoHFz3UjuedWA8FZyrRhUrfbtHDgVSnqvqZe1AwHcKVdzUWlZg5iS2-PcXRw-RsBktgEddJ3tYRjRaCkV4xXVmVRH0sUBMYI3uxi2Nu4No-bgzWzMnzdz8HYoZCu58-Z3h0VnOx9t7wL-tedTBFVcZW5x5CA__BkgGnQBegdtiNmoaYfw765vfO2I5Q</recordid><startdate>2011</startdate><enddate>2011</enddate><creator>Toft, Henrik Stensgaard</creator><creator>Branner, Kim</creator><creator>Berring, Peter</creator><creator>Sørensen, John Dalsgaard</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope></search><sort><creationdate>2011</creationdate><title>Defect distribution and reliability assessment of wind turbine blades</title><author>Toft, Henrik Stensgaard ; Branner, Kim ; Berring, Peter ; Sørensen, John Dalsgaard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c377t-5cb5693ebc48b52f26be3fa52871e6d8fd4e20375ff80f59ce3e2c7c9236859e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Applied sciences</topic><topic>Building failures (cracks, physical changes, etc.)</topic><topic>Buildings. Public works</topic><topic>Computation methods. Tables. Charts</topic><topic>Defects</topic><topic>Delamination</topic><topic>Durability. Pathology. Repairing. Maintenance</topic><topic>Energy</topic><topic>Exact sciences and technology</topic><topic>Natural energy</topic><topic>Probabilistic methods</topic><topic>Reliability</topic><topic>Structural analysis. Stresses</topic><topic>System effects</topic><topic>Wind energy</topic><topic>Wind turbine blades</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Toft, Henrik Stensgaard</creatorcontrib><creatorcontrib>Branner, Kim</creatorcontrib><creatorcontrib>Berring, Peter</creatorcontrib><creatorcontrib>Sørensen, John Dalsgaard</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><jtitle>Engineering structures</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Toft, Henrik Stensgaard</au><au>Branner, Kim</au><au>Berring, Peter</au><au>Sørensen, John Dalsgaard</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Defect distribution and reliability assessment of wind turbine blades</atitle><jtitle>Engineering structures</jtitle><date>2011</date><risdate>2011</risdate><volume>33</volume><issue>1</issue><spage>171</spage><epage>180</epage><pages>171-180</pages><issn>0141-0296</issn><eissn>1873-7323</eissn><coden>ENSTDF</coden><abstract>In this paper, two stochastic models for the distribution of defects in wind turbine blades are proposed. The first model assumes that the individual defects are completely randomly distributed in the blade. The second model assumes that the defects occur in clusters of different size, based on the assumption that one error in the production process tends to trigger several defects. For both models, additional information, such as number, type, and size of the defects, is included as stochastic variables.
In a numerical example, the reliability is estimated for a generic wind turbine blade model both with and without defects in terms of delaminations. The reliability of the blade decreases when defects are included. However, the distribution of the defects influences how much the reliability is decreased. It is also shown how non-destructive inspection (NDI) after production can be used to update the reliability for the wind turbine blade using Bayesian statistics.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.engstruct.2010.10.002</doi><tpages>10</tpages></addata></record> |
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| subjects | Applied sciences Building failures (cracks, physical changes, etc.) Buildings. Public works Computation methods. Tables. Charts Defects Delamination Durability. Pathology. Repairing. Maintenance Energy Exact sciences and technology Natural energy Probabilistic methods Reliability Structural analysis. Stresses System effects Wind energy Wind turbine blades |
| title | Defect distribution and reliability assessment of wind turbine blades |
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