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Title: An Evaluation Study of EMD, EEMD, and VMD For Chatter Detection in Milling
Authors: Seyrek, Pelin
Sener, Batihan
Özbayoğlu, Ahmet Murat
Ünver, Hakkı Özgür
Keywords: Milling
Chatter Detection
Empirical Mode Decomposition (EMD)
Ensemble Empirical Mode Decomposition (EEMD)
Variational Mode Decomposition (VMD)
Empirical Mode Decomposition
Denoising Method
Wavelet Packets
Issue Date: 2022
Publisher: Elsevier Science Bv
Source: 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.
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.
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
ISSN: 1877-0509
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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