Recent Advances in the Use of eXplainable Artificial Intelligence Techniques for Wind Turbine Systems Condition Monitoring

There is a good probability that wind turbines will emerge as one of the predominant technologies for electricity production in the upcoming decades [...]

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Electronics (Basel) 2023-08, Vol.12 (16), p.3509
Hauptverfasser: Astolfi, Davide, De Caro, Fabrizio, Vaccaro, Alfredo
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 16
container_start_page 3509
container_title Electronics (Basel)
container_volume 12
creator Astolfi, Davide
De Caro, Fabrizio
Vaccaro, Alfredo
description There is a good probability that wind turbines will emerge as one of the predominant technologies for electricity production in the upcoming decades [...]
doi_str_mv 10.3390/electronics12163509
format Article
fullrecord <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2857011783</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A762480870</galeid><sourcerecordid>A762480870</sourcerecordid><originalsourceid>FETCH-LOGICAL-c361t-7b59dca805facd3250d4475cd2e6e755864aa67e052cc8bc2ca0262fa4c1d6373</originalsourceid><addsrcrecordid>eNptkU1rGzEQhpfSQIPrX5CLoGen-litdo_G9CPgEGgdktsij0bOhLXkSnLB-fVRcA85dOYww_A-My9M01wJfq3UwL_ihFBSDARZSNEpzYcPzaXkZlgMcpAf3_WfmnnOz7zGIFSv-GXz8gsBQ2FL99cGwMwosPKE7D4ji57h42GyFOx2QrZMhTwB2YndhILTRDusCNsgPAX6c6ywj4k9UHBsc0xbCsh-n3LBfWarGBwVioHdVqMlJgq7z82Ft1PG-b86a-6_f9usfi7Wdz9uVsv1AlQnysJs9eDA9lx7C05JzV3bGg1OYodG675rre0Mci0B-i1IsFx20tsWhOuUUbPmy3nvIcU3l2V8jscU6slR9tpwIUyvqur6rNrZCUcKPpZkoabDPUEM6KnOl6aTbc97wyugzgCkmHNCPx4S7W06jYKPb48Z__MY9QoFoIWd</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2857011783</pqid></control><display><type>article</type><title>Recent Advances in the Use of eXplainable Artificial Intelligence Techniques for Wind Turbine Systems Condition Monitoring</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Astolfi, Davide ; De Caro, Fabrizio ; Vaccaro, Alfredo</creator><creatorcontrib>Astolfi, Davide ; De Caro, Fabrizio ; Vaccaro, Alfredo</creatorcontrib><description>There is a good probability that wind turbines will emerge as one of the predominant technologies for electricity production in the upcoming decades [...]</description><identifier>ISSN: 2079-9292</identifier><identifier>EISSN: 2079-9292</identifier><identifier>DOI: 10.3390/electronics12163509</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Air-turbines ; Artificial intelligence ; Condition monitoring ; Electricity ; Explainable artificial intelligence ; Identity formation ; Maintenance and repair ; Temperature ; Turbines ; Variables ; Wind farms ; Wind power ; Wind turbines</subject><ispartof>Electronics (Basel), 2023-08, Vol.12 (16), p.3509</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c361t-7b59dca805facd3250d4475cd2e6e755864aa67e052cc8bc2ca0262fa4c1d6373</citedby><cites>FETCH-LOGICAL-c361t-7b59dca805facd3250d4475cd2e6e755864aa67e052cc8bc2ca0262fa4c1d6373</cites><orcidid>0000-0001-7256-2705 ; 0000-0001-5577-7544</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Astolfi, Davide</creatorcontrib><creatorcontrib>De Caro, Fabrizio</creatorcontrib><creatorcontrib>Vaccaro, Alfredo</creatorcontrib><title>Recent Advances in the Use of eXplainable Artificial Intelligence Techniques for Wind Turbine Systems Condition Monitoring</title><title>Electronics (Basel)</title><description>There is a good probability that wind turbines will emerge as one of the predominant technologies for electricity production in the upcoming decades [...]</description><subject>Air-turbines</subject><subject>Artificial intelligence</subject><subject>Condition monitoring</subject><subject>Electricity</subject><subject>Explainable artificial intelligence</subject><subject>Identity formation</subject><subject>Maintenance and repair</subject><subject>Temperature</subject><subject>Turbines</subject><subject>Variables</subject><subject>Wind farms</subject><subject>Wind power</subject><subject>Wind turbines</subject><issn>2079-9292</issn><issn>2079-9292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNptkU1rGzEQhpfSQIPrX5CLoGen-litdo_G9CPgEGgdktsij0bOhLXkSnLB-fVRcA85dOYww_A-My9M01wJfq3UwL_ihFBSDARZSNEpzYcPzaXkZlgMcpAf3_WfmnnOz7zGIFSv-GXz8gsBQ2FL99cGwMwosPKE7D4ji57h42GyFOx2QrZMhTwB2YndhILTRDusCNsgPAX6c6ywj4k9UHBsc0xbCsh-n3LBfWarGBwVioHdVqMlJgq7z82Ft1PG-b86a-6_f9usfi7Wdz9uVsv1AlQnysJs9eDA9lx7C05JzV3bGg1OYodG675rre0Mci0B-i1IsFx20tsWhOuUUbPmy3nvIcU3l2V8jscU6slR9tpwIUyvqur6rNrZCUcKPpZkoabDPUEM6KnOl6aTbc97wyugzgCkmHNCPx4S7W06jYKPb48Z__MY9QoFoIWd</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Astolfi, Davide</creator><creator>De Caro, Fabrizio</creator><creator>Vaccaro, Alfredo</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0001-7256-2705</orcidid><orcidid>https://orcid.org/0000-0001-5577-7544</orcidid></search><sort><creationdate>20230801</creationdate><title>Recent Advances in the Use of eXplainable Artificial Intelligence Techniques for Wind Turbine Systems Condition Monitoring</title><author>Astolfi, Davide ; De Caro, Fabrizio ; Vaccaro, Alfredo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c361t-7b59dca805facd3250d4475cd2e6e755864aa67e052cc8bc2ca0262fa4c1d6373</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Air-turbines</topic><topic>Artificial intelligence</topic><topic>Condition monitoring</topic><topic>Electricity</topic><topic>Explainable artificial intelligence</topic><topic>Identity formation</topic><topic>Maintenance and repair</topic><topic>Temperature</topic><topic>Turbines</topic><topic>Variables</topic><topic>Wind farms</topic><topic>Wind power</topic><topic>Wind turbines</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Astolfi, Davide</creatorcontrib><creatorcontrib>De Caro, Fabrizio</creatorcontrib><creatorcontrib>Vaccaro, Alfredo</creatorcontrib><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Electronics (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Astolfi, Davide</au><au>De Caro, Fabrizio</au><au>Vaccaro, Alfredo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Recent Advances in the Use of eXplainable Artificial Intelligence Techniques for Wind Turbine Systems Condition Monitoring</atitle><jtitle>Electronics (Basel)</jtitle><date>2023-08-01</date><risdate>2023</risdate><volume>12</volume><issue>16</issue><spage>3509</spage><pages>3509-</pages><issn>2079-9292</issn><eissn>2079-9292</eissn><abstract>There is a good probability that wind turbines will emerge as one of the predominant technologies for electricity production in the upcoming decades [...]</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/electronics12163509</doi><orcidid>https://orcid.org/0000-0001-7256-2705</orcidid><orcidid>https://orcid.org/0000-0001-5577-7544</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2079-9292
ispartof Electronics (Basel), 2023-08, Vol.12 (16), p.3509
issn 2079-9292
2079-9292
language eng
recordid cdi_proquest_journals_2857011783
source MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals
subjects Air-turbines
Artificial intelligence
Condition monitoring
Electricity
Explainable artificial intelligence
Identity formation
Maintenance and repair
Temperature
Turbines
Variables
Wind farms
Wind power
Wind turbines
title Recent Advances in the Use of eXplainable Artificial Intelligence Techniques for Wind Turbine Systems Condition Monitoring
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T16%3A15%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Recent%20Advances%20in%20the%20Use%20of%20eXplainable%20Artificial%20Intelligence%20Techniques%20for%20Wind%20Turbine%20Systems%20Condition%20Monitoring&rft.jtitle=Electronics%20(Basel)&rft.au=Astolfi,%20Davide&rft.date=2023-08-01&rft.volume=12&rft.issue=16&rft.spage=3509&rft.pages=3509-&rft.issn=2079-9292&rft.eissn=2079-9292&rft_id=info:doi/10.3390/electronics12163509&rft_dat=%3Cgale_proqu%3EA762480870%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2857011783&rft_id=info:pmid/&rft_galeid=A762480870&rfr_iscdi=true