An Evaluation Study of EMD, EEMD, and VMD For Chatter Detection in Milling

Seyrek, Pelin; Şener, Batıhan; Özbayoğlu, A. Murat; Ünver, Hakkı Özgür

doi:10.1016/j.procs.2022.01.215

Cited by 22 publications

(9 citation statements)

References 24 publications

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“…Following the heterogeneous market hypothesis by Müller et al (1993), 5 agents in financial markets have varying decision-making timescales and so this study employs the EEMD to decompose the time series of the currencies into varying times and frequencies. The EEMD technique is preferred over other decomposition methods such as empirical mode decomposition (EMD), the Variational Mode Decomposition (VMD) and the Maximal overlap discrete wavelet transform (MODWT) because the EEMD technique provides powerful tool for denoising seismic signals (Gaci, 2016;Seyrek et al, 2022;Xu & Niu, 2022). While many data analysis techniques have unsuccessfully attempted to remove white noise from time series data, the EEMD adds white noise to remove weak signals (to keep the true signal).…”

Section: Methodsmentioning

confidence: 99%

Cryptocurrency and African fiat currencies: A peaceful coexistence?

Kumah

2023

Economic Notes

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This study examines the asymmetric behaviour of Bitcoin relative to six major African fiat currencies (Egyptian Pound, Cedi, ZAR, Naira, Rupee and Dinar) for the period 10 August 2015 to 31 December 2022. The time and frequency information in the time series of the currencies were captured applying the ensemble empirical mode decomposition. The quantile regression (QR) and quantile‐in‐quantile regression (QQR) were applied on the decomposed series to examine the connections among the currencies at different currency regimes across time. The empirical results show that both QR and QQR can adequately capture the time‐varying asymmetric behaviour of the currencies across time. The results range from weak to very strong dependencies albeit both negative and positive across different quantiles. Our findings suggest that except for ZAR, Bitcoin is a viable alternative currency to African reserve currencies from the medium‐term since it can hedge depreciation and forex risk of the fiat currencies. Based on the findings of this study, we recommend that forex traders and policymakers in Africa should adopt Bitcoin as an alternative currency to African currencies in the medium‐term to mitigate currency crises in the continent.

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Section: Methodsmentioning

confidence: 99%

Cryptocurrency and African fiat currencies: A peaceful coexistence?

Kumah

2023

Economic Notes

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“…Both works show that the selection of decomposition parameters could affect the value of the chatter index. It was shown that VMD has a better performance in chatter detection than EMD and EEMD, while Seyrek et al [339] recently presented a detailed comparison of the results with these 3 techniques. Hence, VMD is one of the most acceptable methods for signal processing currently.…”

Section: Time-frequency Domain Analysismentioning

confidence: 99%

Chatter detection in milling processes—a review on signal processing and condition classification

Navarro-Devia

Chen

Dao

et al. 2023

Int J Adv Manuf Technol

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Among the diverse challenges in machining processes, chatter has a significant detrimental effect on surface quality and tool life, and it is a major limitation factor in achieving higher material removal rate. Early detection of chatter occurrence is considered a key element in the milling process automation. Online detection of chatter onset has been continually investigated over several decades, along with the development of new signal processing and machining condition classification approaches. This paper presents a review of the literature on chatter detection in milling, providing a comprehensive analysis of the reported methods for sensing and testing parameter design, signal processing and various features proposed as chatter indicators. It discusses data-driven approaches, including the use of different techniques in the time–frequency domain, feature extraction, and machining condition classification. The review outlines the potential of using multiple sensors and information fusion with machine learning. To conclude, research trends, challenges and future perspectives are presented, with the recommendation to study the tool wear effects, and chatter detection at dissimilar milling conditions, while utilization of considerable large datasets—Big Data—under the Industry 4.0 framework and the development of machining Digital Twin capable of real-time chatter detection are considered as key enabling technologies for intelligent manufacturing.

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“…No The authors use these techniques to analyze the signal in several areas of machining, such as milling [77], [78] [79], turning [75], and rotor system [80]. [43] is a review of research on vibrational chatter in turning operations.…”

Section: Nonstationarymentioning

confidence: 99%

Review of AI-based methods for chatter detection in machining based on bibliometric analysis

Kounta

Arnaud

Kamsu-Foguem

et al. 2022

Int J Adv Manuf Technol

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HIGHLIGHTS• Bibliometric analysis on chatter detection techniques in machining processes.• Effectiveness of AI methods combined with transformation and decomposition techniques.• Research areas mainly cover manufacturing, mechanics, and automation control systems.• Application of signal processing techniques in chatter detection with their advantages.• Challenges of deep learning models to solve problems of performance and explainability.

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An Evaluation Study of EMD, EEMD, and VMD For Chatter Detection in Milling

Cited by 22 publications

References 24 publications

Cryptocurrency and African fiat currencies: A peaceful coexistence?

Cryptocurrency and African fiat currencies: A peaceful coexistence?

Chatter detection in milling processes—a review on signal processing and condition classification

Review of AI-based methods for chatter detection in machining based on bibliometric analysis

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