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https://hdl.handle.net/20.500.11851/8750
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Seyrek, Pelin | - |
dc.contributor.author | Sener, Batihan | - |
dc.contributor.author | Özbayoğlu, Ahmet Murat | - |
dc.contributor.author | Ünver, Hakkı Özgür | - |
dc.date.accessioned | 2022-07-30T16:57:01Z | - |
dc.date.available | 2022-07-30T16:57:01Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Seyrek, P., Şener, B., Özbayoğlu, A. M., & Ünver, H. Ö. (2022). An Evaluation Study of EMD, EEMD, and VMD For Chatter Detection in Milling. Procedia Computer Science, 200, 160-174. | en_US |
dc.identifier.issn | 1877-0509 | - |
dc.identifier.uri | https://doi.org/10.1016/j.procs.2022.01.215 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/8750 | - |
dc.description | 3rd International Conference on Industry 4.0 and Smart Manufacturing (ISM) -- NOV 17-19, 2021 -- Upper Austria Univ Appl Sci, Hagenberg Campus, Linz, AUSTRIA | en_US |
dc.description.abstract | In modem machining processes, chatter is an inherent phenomenon that hinders efficiency, productivity, and automation. Numerous methods have been proposed using analytical, computational, and artificial intelligence methods to detect and avoid chatter during milling. The vibration signals generated during machining are of non-stationary and non-linearity nature. Hence solely time or frequency domain analysis are not adequate methods for chatter detection. This study investigates the performance of more advanced mode decomposition methods and compares them. Three decomposition methods, namely, empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and variational mode decomposition (VMD), are used to decompose and identify chatter frequency bands. After decomposition, Hilbert-Huang transform (HHT) was applied for visualization. The comparative results indicate that EEMD or VMD decomposition methods performed better than EMD for intelligent chatter detection. (C) 2022 The Authors. Published by Elsevier B.V. | en_US |
dc.description.sponsorship | Scientific and Technological Research Council of Turkey (TUBITAK) [118M414] | en_US |
dc.description.sponsorship | This study was funded by The Scientific and Technological Research Council of Turkey (TUBITAK) through project grant no. 118M414. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier Science Bv | en_US |
dc.relation.ispartof | 3rd International Conference On Industry 4.0 and Smart Manufacturing | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Milling | en_US |
dc.subject | Chatter Detection | en_US |
dc.subject | Empirical Mode Decomposition (EMD) | en_US |
dc.subject | Ensemble Empirical Mode Decomposition (EEMD) | en_US |
dc.subject | Variational Mode Decomposition (VMD) | en_US |
dc.subject | Empirical Mode Decomposition | en_US |
dc.subject | Denoising Method | en_US |
dc.subject | Wavelet Packets | en_US |
dc.subject | Identification | en_US |
dc.title | An Evaluation Study of Emd, Eemd, and Vmd for Chatter Detection in Milling | en_US |
dc.type | Conference Object | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Yapay Zeka Mühendisliği Bölümü | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Makine Mühendisliği Bölümü | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Artificial Intelligence Engineering | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Mechanical Engineering | en_US |
dc.identifier.volume | 200 | en_US |
dc.identifier.startpage | 160 | en_US |
dc.identifier.endpage | 174 | en_US |
dc.authorid | Ozbayoglu, Ahmet Murat/0000-0001-7998-5735 | - |
dc.identifier.wos | WOS:000777601300017 | en_US |
dc.identifier.scopus | 2-s2.0-85127803584 | en_US |
dc.institutionauthor | Özbayoğlu, Ahmet Murat | - |
dc.institutionauthor | Ünver, Hakkı Özgür | - |
dc.identifier.doi | 10.1016/j.procs.2022.01.215 | - |
dc.authorwosid | Ozbayoglu, Ahmet Murat/H-2328-2011 | - |
dc.authorscopusid | 57565898600 | - |
dc.authorscopusid | 57220450360 | - |
dc.authorscopusid | 6505999525 | - |
dc.authorscopusid | 6603873269 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | - | - |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.1. Department of Artificial Intelligence Engineering | - |
crisitem.author.dept | 02.7. Department of Mechanical Engineering | - |
Appears in Collections: | Makine Mühendisliği Bölümü / Department of Mechanical Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection Yapay Zeka Mühendisliği Bölümü / Department of Artificial Intelligence Engineering |
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