Title: Development of a robust indicator for online chatter detection

Authors: Dialoke Ejiofor Matthew; Hongrui Cao; Jianghai Shi

Addresses: National and Local Joint Engineering Research Center of Equipment Operation Safety and Intelligent Monitoring, Xi'an Jiaotong University, Xi'an, 710049, China; School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; Qingdao Aerospace Power Structure Safety Institute, Qingdao, 266000, China ' National and Local Joint Engineering Research Center of Equipment Operation Safety and Intelligent Monitoring, Xi'an Jiaotong University, Xi'an, 710049, China; School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; Qingdao Aerospace Power Structure Safety Institute, Qingdao, 266000, China ' National and Local Joint Engineering Research Center of Equipment Operation Safety and Intelligent Monitoring, Xi'an Jiaotong University, Xi'an, 710049, China; School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; Qingdao Aerospace Power Structure Safety Institute, Qingdao, 266000, China

Abstract: During the milling process, chatter is one of the most uncontrollable and unwanted occurrences. To prevent damage to the workpiece and to monitor and detect chatter as quickly as possible, a reliable indicator is essential. This paper proposes a robust root mean square (RRMS) indicator for online chatter identification. Using weighted techniques, the two-time domain indicators root mean square (RMS) and kurtosis (K) are combined to develop the proposed indicator, RRMS, with improved detection accuracy. The short-time Fourier transform (STFT) was used to visualise the changing frequency components in the time-frequency representation (TFR). The efficacy of the proposed indicator for online detection was confirmed by a series of milling tests. The 3-sigma rule is used to calculate the threshold, and the RRMS is employed for detection. Because the results demonstrate a heightened sensitivity to chatter, we concluded that RRMS is extremely suitable for online detection.

Keywords: chatter detection; acoustic signal; weighted technique; variable cutting depth; VMD; variational mode decomposition.

DOI: 10.1504/IJMMS.2024.143009

International Journal of Mechatronics and Manufacturing Systems, 2024 Vol.17 No.2, pp.132 - 149

Received: 29 Dec 2023
Accepted: 23 Mar 2024
Published online: 02 Dec 2024 *

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