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Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials, Volume 32, Number 3(1) (2020)
Copyright(C) MYU K.K.
pp. 873-884
S&M2144 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2671
Published: March 10, 2020

Acoustic Signal Analysis by Teager–Huang Transform for Milling Chatter Recognition [PDF]

Rong-Mao Lee, Yi-Hsing Yu, Cheng-Chi Wang, Tsung-Chia Chen, and Pongpon Nilaphruek

(Received February 3, 2019; Accepted December 23, 2019)

Keywords: milling vibration, milling noise, time-frequency domain, Teager–Huang transform

Many types of sensor have been utilized to monitor milling vibration, and many analysis methods are devoted to the investigation of milling vibration or milling dynamics. In this work, a noncontact sensor and a time-frequency domain analysis method were applied to identify the state of milling vibration. A microphone was employed in practical tests to record the milling dynamics. The Teager-Huang transform (THT) was adopted for the acoustic signal analysis owing to its high resolution in the time-frequency domain. The potential frequency range for the analysis of milling dynamics is reported in this work to improve the recognition accuracy of milling vibration limited by the effect of environmental noise. The THT was used to distinguish the chatter state from the normal milling dynamics. In addition, the statistical index called coefficient of variation (CV) was applied to define the threshold of chatter occurrence. Milling experiments (including dry and wet cuttings) were performed to verify the proposed chatter detection method.

Corresponding author: Rong-Mao Lee


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Rong-Mao Lee, Yi-Hsing Yu, Cheng-Chi Wang, Tsung-Chia Chen, and Pongpon Nilaphruek, Acoustic Signal Analysis by Teager–Huang Transform for Milling Chatter Recognition, Sens. Mater., Vol. 32, No. 3, 2020, p. 873-884.



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