Combined Use of Modal Analysis and Machine Learning for Materials Classification

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dc.contributor.authorAbdelkader, Mohameden
dc.contributor.authorNoman, Muhammad Tayyaben
dc.contributor.authorAmor, Nesrineen
dc.contributor.authorPetru, Michalen
dc.contributor.authorMahmood, Aamiren
dc.date.accessioned2021-08-09T16:55:14Zen
dc.date.available2021-08-09T16:55:14Zen
dc.date.issued2021-07-30en
dc.date.updated2021-08-06T15:20:01Zen
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.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationAbdelkader, M.; Noman, M.T.; Amor, N.; Petru, M.; Mahmood, A. Combined Use of Modal Analysis and Machine Learning for Materials Classification. Materials 2021, 14, 4270.en
dc.identifier.doihttps://doi.org/10.3390/ma14154270en
dc.identifier.urihttp://hdl.handle.net/10919/104614en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectisotropicen
dc.subjectanisotropicen
dc.subjectorthotropicen
dc.subjectmodal analysisen
dc.subjectresonance frequencyen
dc.subjectmode shapesen
dc.titleCombined Use of Modal Analysis and Machine Learning for Materials Classificationen
dc.title.serialMaterialsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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