Chatter detection in milling process based on the energy entropy of VMD and WPD. (September 2016)

• Record Type: Journal Article
• Authors: Zhang, Zhao; Li, Hongguang; Meng, Guang; Tu, Xiaotong; Cheng, Changming
• Is Part Of: International journal of machine tools & manufacture. Volume 108(2016:Sep.)
• Page Start: 106
• Page End: 112
• Publication Date: 2016-09
• Subjects: Chatter detection -- Variational mode decomposition -- Wavelet packet decomposition -- Energy entropy -- Cutting force; Machine-tools -- Periodicals; Manufacturing processes -- Periodicals; Machines-outils -- Périodiques; Fabrication -- Périodiques; Electronic journals; 621.902
• DOI: 10.1016/j.ijmachtools.2016.06.002
• Languages: English
• ISSNs: 0890-6955

Abstract

Abstract: This paper presents a novel approach to detect the milling chatter based on energy entropy. By using variational mode decomposition and wavelet packet decomposition, the cutting force signal is decomposed into two group of sub-signals respectively, and each component has limited bandwidth in spectral domain. Since milling chatter is characterized by the change of frequency and energy distribution. Therefore the energy features extracted from the two group of sub-signals are considered and the energy entropies are obtained, which can be utilized to demonstrate the condition of the milling system synthetically. Several milling tests are conducted and the results show that the proposed method can effectively detect the chatter at an early stage. Highlights: A new approach is presented to detect milling chatter in peripheral milling. The non-stationary chatter signal is decomposed based on the VMD and WPD. Energy entropy are utilized to demonstrate the condition of milling system. The method has an excellent performance for chatter identification.