dc.contributor.author | Abdelkader, Mohamed Abdelkader Fawzy | |
dc.contributor.author | Noman, Muhammad Tayyab | |
dc.contributor.author | Amor, Nesrine | |
dc.contributor.author | Petru, Michal | |
dc.contributor.author | Mahmood, Aamir | |
dc.date.accessioned | 2023-09-18T16:08:39Z | |
dc.date.available | 2023-09-18T16:08:39Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 1996-1944 | |
dc.identifier.other | (WOS_ID)000682101300001 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/111744 | |
dc.description.abstract | The 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.format | PDF | |
dc.format.extent | p. 1-15 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.relation.isreferencedby | Scopus | |
dc.relation.isreferencedby | DOAJ | |
dc.source.uri | https://doi.org/10.3390/ma14154270 | |
dc.title | Combined use of modal analysis and machine learning for materials classification | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.accessRights | 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/). | |
dcterms.license | Creative Commons – Attribution – 4.0 International | |
dcterms.references | 33 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Technical University of Liberec Vilniaus Gedimino technikos universitetas Valstybinis mokslinių tyrimų institutas Fizinių ir technologijos mokslų centras | |
dc.contributor.institution | Technical University of Liberec | |
dc.contributor.faculty | Mechanikos fakultetas / Faculty of Mechanics | |
dc.subject.researchfield | T 009 - Mechanikos inžinerija / Mechanical enginering | |
dc.subject.researchfield | T 008 - Medžiagų inžinerija / Material engineering | |
dc.subject.vgtuprioritizedfields | IK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems | |
dc.subject.ltspecializations | L104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies | |
dc.subject.en | isotropic | |
dc.subject.en | anisotropic | |
dc.subject.en | orthotropic | |
dc.subject.en | modal analysis | |
dc.subject.en | resonance frequency | |
dc.subject.en | mode shapes | |
dcterms.sourcetitle | Materials | |
dc.description.issue | iss. 15 | |
dc.description.volume | vol. 14 | |
dc.publisher.name | MDPI | |
dc.publisher.city | Basel | |
dc.identifier.doi | 000682101300001 | |
dc.identifier.doi | 10.3390/ma14154270 | |
dc.identifier.elaba | 102298850 | |