Detection of modulated chatter using moving average difference spectrum analysis. (20th January 2022)

• Record Type: Journal Article
• Authors: Xu, Xiaoqiang; Zhou, Tianyu; Wan, Liyou; Hu, Hongwei; Hu, Yongle
• Is Part Of: Journal of sound and vibration. Volume 517(2022)
• Publication Date: 2022-01-20
• Subjects: Chatter monitoring -- Moving average -- Difference spectrum analysis -- Monotonicity analysis -- Wavelet packet-energy entropy; Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2021.116568
• Languages: English
• ISSNs: 0022-460X

Abstract

Highlights: MADSA is proposed for early detection of modulated chatter from vibration signal. Bevel gear milling experiment is used to validate the proposed method. MADSA outperforms traditional method in terms of capability and accuracy. Abstract: Chatter monitoring is an essential requirement for high-precision machining systems. Chatter vibration is characterized by amplitude modulation when the beat-frequency effect or geometric eccentricities exist, which hinders methods based on the transient characteristic index. Here, moving average difference spectrum analysis (MADSA) is proposed for detection of modulated chatter; the method can detect chatter frequency and track its amplitude from low signal-to-noise vibration signals early on. MADSA utilizes a moving average to smooth the amplitude trend of chatter frequency candidates obtained by the difference spectrum analysis, and the chatter frequency is detected using monotonicity analysis. MADSA was validated in both simulations and gear-milling machine experiments, and comparisons between wavelet packet-energy entropy method and MADSA are described, to illustrate the performance of the latter.