Prediction of tensile strength of friction stir welded 6061 Al plates

The present paper investigates the prediction of tensile strength after friction stir welding (FSW) using artificial neural network (ANN) in the MATLAB program. The experimental results are used to develop the mathematical model. The combined influence of weld-ing speed, rotation speed, and axial fo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:中国焊接 2019-09, Vol.28 (3), p.1-6
Hauptverfasser: Farghaly Ahmed A, El-Nikhaily Ahmed E, Essa A R S
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 6
container_issue 3
container_start_page 1
container_title 中国焊接
container_volume 28
creator Farghaly Ahmed A
El-Nikhaily Ahmed E
Essa A R S
description The present paper investigates the prediction of tensile strength after friction stir welding (FSW) using artificial neural network (ANN) in the MATLAB program. The experimental results are used to develop the mathematical model. The combined influence of weld-ing speed, rotation speed, and axial force on the tensile strength of 6061 Al plates is simulated. Results of the tensile test are used to train and test the ANN model. A multi-layer solution is developed using the ANN model to predict tensile strength. Back propagation (BP) method is initially trained using 80% of the experimental data, then, testing is performed with the rest of the data. Results indicate that predicted values are close to the corresponding measured values.
doi_str_mv 10.12073/j.cw.20190617001
format Article
fullrecord <record><control><sourceid>wanfang_jour</sourceid><recordid>TN_cdi_wanfang_journals_zghj_e201903001</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><wanfj_id>zghj_e201903001</wanfj_id><sourcerecordid>zghj_e201903001</sourcerecordid><originalsourceid>FETCH-LOGICAL-s1021-7f5f0ba7de8f3e59f0ee3adf77d69f5dfea5a64207850f0e7fb135ae0607e4953</originalsourceid><addsrcrecordid>eNotjz1rwzAURTW00DTtD-imrZPdJ8uyojGE9AMC7ZDMRonec2yEXCQVQ3993TbThXvhXA5jDwJKUYGWT0N5msoKhIFGaABxxRYCoC6UrMUNu01pAJBGg16w7UdE159yPwY-Es8YUu-RpxwxdPn821G87Cn3kU_oHTrezGi-9vzT24zpjl2T9QnvL7lkh-ftfvNa7N5f3jbrXZEEVKLQpAiOVjtckURlCBCldaS1awwpR2iVberZYaVgHjUdhVQWoQGNtVFyyR7_uZMNZEPXDuNXDPNj-92dhxb_nOVsLH8AQXFNCA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Prediction of tensile strength of friction stir welded 6061 Al plates</title><source>Alma/SFX Local Collection</source><creator>Farghaly Ahmed A ; El-Nikhaily Ahmed E ; Essa A R S</creator><creatorcontrib>Farghaly Ahmed A ; El-Nikhaily Ahmed E ; Essa A R S</creatorcontrib><description>The present paper investigates the prediction of tensile strength after friction stir welding (FSW) using artificial neural network (ANN) in the MATLAB program. The experimental results are used to develop the mathematical model. The combined influence of weld-ing speed, rotation speed, and axial force on the tensile strength of 6061 Al plates is simulated. Results of the tensile test are used to train and test the ANN model. A multi-layer solution is developed using the ANN model to predict tensile strength. Back propagation (BP) method is initially trained using 80% of the experimental data, then, testing is performed with the rest of the data. Results indicate that predicted values are close to the corresponding measured values.</description><identifier>ISSN: 1004-5341</identifier><identifier>DOI: 10.12073/j.cw.20190617001</identifier><language>eng</language><publisher>Mechanical Engineering Department,Egyptian Academy for Engineering &amp; Advanced Technology,Affiliated to Ministry of Military Production,3056,Egypt</publisher><ispartof>中国焊接, 2019-09, Vol.28 (3), p.1-6</ispartof><rights>Copyright © Wanfang Data Co. Ltd. All Rights Reserved.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://www.wanfangdata.com.cn/images/PeriodicalImages/zghj-e/zghj-e.jpg</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Farghaly Ahmed A</creatorcontrib><creatorcontrib>El-Nikhaily Ahmed E</creatorcontrib><creatorcontrib>Essa A R S</creatorcontrib><title>Prediction of tensile strength of friction stir welded 6061 Al plates</title><title>中国焊接</title><description>The present paper investigates the prediction of tensile strength after friction stir welding (FSW) using artificial neural network (ANN) in the MATLAB program. The experimental results are used to develop the mathematical model. The combined influence of weld-ing speed, rotation speed, and axial force on the tensile strength of 6061 Al plates is simulated. Results of the tensile test are used to train and test the ANN model. A multi-layer solution is developed using the ANN model to predict tensile strength. Back propagation (BP) method is initially trained using 80% of the experimental data, then, testing is performed with the rest of the data. Results indicate that predicted values are close to the corresponding measured values.</description><issn>1004-5341</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNotjz1rwzAURTW00DTtD-imrZPdJ8uyojGE9AMC7ZDMRonec2yEXCQVQ3993TbThXvhXA5jDwJKUYGWT0N5msoKhIFGaABxxRYCoC6UrMUNu01pAJBGg16w7UdE159yPwY-Es8YUu-RpxwxdPn821G87Cn3kU_oHTrezGi-9vzT24zpjl2T9QnvL7lkh-ftfvNa7N5f3jbrXZEEVKLQpAiOVjtckURlCBCldaS1awwpR2iVberZYaVgHjUdhVQWoQGNtVFyyR7_uZMNZEPXDuNXDPNj-92dhxb_nOVsLH8AQXFNCA</recordid><startdate>20190925</startdate><enddate>20190925</enddate><creator>Farghaly Ahmed A</creator><creator>El-Nikhaily Ahmed E</creator><creator>Essa A R S</creator><general>Mechanical Engineering Department,Egyptian Academy for Engineering &amp; Advanced Technology,Affiliated to Ministry of Military Production,3056,Egypt</general><general>Mechanical Department,Faculty of Industrial Education,Suez University,43527,Egypt%Mechanical Department,Faculty of Industrial Education,Suez University,43527,Egypt</general><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20190925</creationdate><title>Prediction of tensile strength of friction stir welded 6061 Al plates</title><author>Farghaly Ahmed A ; El-Nikhaily Ahmed E ; Essa A R S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-s1021-7f5f0ba7de8f3e59f0ee3adf77d69f5dfea5a64207850f0e7fb135ae0607e4953</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Farghaly Ahmed A</creatorcontrib><creatorcontrib>El-Nikhaily Ahmed E</creatorcontrib><creatorcontrib>Essa A R S</creatorcontrib><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>中国焊接</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Farghaly Ahmed A</au><au>El-Nikhaily Ahmed E</au><au>Essa A R S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of tensile strength of friction stir welded 6061 Al plates</atitle><jtitle>中国焊接</jtitle><date>2019-09-25</date><risdate>2019</risdate><volume>28</volume><issue>3</issue><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>1004-5341</issn><abstract>The present paper investigates the prediction of tensile strength after friction stir welding (FSW) using artificial neural network (ANN) in the MATLAB program. The experimental results are used to develop the mathematical model. The combined influence of weld-ing speed, rotation speed, and axial force on the tensile strength of 6061 Al plates is simulated. Results of the tensile test are used to train and test the ANN model. A multi-layer solution is developed using the ANN model to predict tensile strength. Back propagation (BP) method is initially trained using 80% of the experimental data, then, testing is performed with the rest of the data. Results indicate that predicted values are close to the corresponding measured values.</abstract><pub>Mechanical Engineering Department,Egyptian Academy for Engineering &amp; Advanced Technology,Affiliated to Ministry of Military Production,3056,Egypt</pub><doi>10.12073/j.cw.20190617001</doi><tpages>6</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1004-5341
ispartof 中国焊接, 2019-09, Vol.28 (3), p.1-6
issn 1004-5341
language eng
recordid cdi_wanfang_journals_zghj_e201903001
source Alma/SFX Local Collection
title Prediction of tensile strength of friction stir welded 6061 Al plates
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T20%3A23%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-wanfang_jour&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prediction%20of%20tensile%20strength%20of%20friction%20stir%20welded%206061%20Al%20plates&rft.jtitle=%E4%B8%AD%E5%9B%BD%E7%84%8A%E6%8E%A5&rft.au=Farghaly%20Ahmed%20A&rft.date=2019-09-25&rft.volume=28&rft.issue=3&rft.spage=1&rft.epage=6&rft.pages=1-6&rft.issn=1004-5341&rft_id=info:doi/10.12073/j.cw.20190617001&rft_dat=%3Cwanfang_jour%3Ezghj_e201903001%3C/wanfang_jour%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_wanfj_id=zghj_e201903001&rfr_iscdi=true