Rodyti trumpą aprašą

dc.contributor.authorAbdelkader, Mohamed Abdelkader Fawzy
dc.contributor.authorNoman, Muhammad Tayyab
dc.contributor.authorAmor, Nesrine
dc.contributor.authorPetru, Michal
dc.contributor.authorMahmood, Aamir
dc.date.accessioned2023-09-18T16:08:39Z
dc.date.available2023-09-18T16:08:39Z
dc.date.issued2021
dc.identifier.issn1996-1944
dc.identifier.other(WOS_ID)000682101300001
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/111744
dc.description.abstractThe present study deals with modal work that is a type of framework for structural dynamic testing of linear structures. Modal analysis is a powerful tool that works on the modal parameters to ensure the safety of materials and eliminate the failure possibilities. The concept of classification through this study is validated for isotropic and orthotropic materials, reaching up to a 100% accuracy when deploying the machine learning approach between the mode number and the associated frequency of the interrelated variables that were extracted from modal analysis performed by ANSYS. This study shows a new classification method dependent only on the knowledge of resonance frequency of a specific material and opens new directions for future developments to create a single device that can identify and classify different engineering materials.eng
dc.formatPDF
dc.format.extentp. 1-15
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyDOAJ
dc.source.urihttps://doi.org/10.3390/ma14154270
dc.titleCombined use of modal analysis and machine learning for materials classification
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis 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/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references33
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionTechnical University of Liberec Vilniaus Gedimino technikos universitetas Valstybinis mokslinių tyrimų institutas Fizinių ir technologijos mokslų centras
dc.contributor.institutionTechnical University of Liberec
dc.contributor.facultyMechanikos fakultetas / Faculty of Mechanics
dc.subject.researchfieldT 009 - Mechanikos inžinerija / Mechanical enginering
dc.subject.researchfieldT 008 - Medžiagų inžinerija / Material engineering
dc.subject.vgtuprioritizedfieldsIK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems
dc.subject.ltspecializationsL104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies
dc.subject.enisotropic
dc.subject.enanisotropic
dc.subject.enorthotropic
dc.subject.enmodal analysis
dc.subject.enresonance frequency
dc.subject.enmode shapes
dcterms.sourcetitleMaterials
dc.description.issueiss. 15
dc.description.volumevol. 14
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000682101300001
dc.identifier.doi10.3390/ma14154270
dc.identifier.elaba102298850


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