A Milling Chatter Identification Method Based on Variational Mode Decomposition and Energy Entropy

Abstract

The invention discloses a milling chatter identification method based on variational mode decomposition and energy entropy, and belongs to the technical field of machine tool processing chatter identification. It includes the following steps: S1. Establish a mathematical model of VMD; S2. Establish a mathematical model of energy entropy; S3. Conduct three sets of milling processing experiments representing three cutting states: stable cutting, weak chatter and severe chatter. A force meter is used to obtain three sets of milling force signals; S4, conduct FFT analysis on the three sets of milling force signals, and prove that the three sets of milling force signals respectively represent the processing in stable cutting, weak chatter and severe chatter states; S5, based on kurtosis The automatic selection method of VMD parameters of the value determines the optimal number of modes K and penalty factor α for VMD decomposition; S6. Find the instantaneous frequencies of multiple IMFs and determine the milling chatter characteristic frequency band; S7. Use hammering experiments to obtain tool modes ; S8. Extract the flutter feature vector for each IMF based on energy entropy. The invention improves the VMD decomposition effect and realizes automatic identification of chatter.

Description

technical field [0001] The invention belongs to the technical field of machine tool machining chatter recognition, and relates to a milling chatter recognition method based on variational mode decomposition and energy entropy. Background technique [0002] In order to improve the material removal rate and reduce the cutting force, high-speed milling is widely used in the aerospace industry. Machine tool chatter originates from the self-excitation mechanism in chip formation. A certain mode of the tool-workpiece system is initially excited by the cutting force, which generates chatter at a frequency close to but not equal to the main structure frequency of the machining system. Chatter reduces surface quality, productivity, and causes tool wear. For the chatter problem of the machining process system, many scholars have proposed methods such as chatter stability prediction, identification, and suppression, but for machine tool operators, it is difficult to implement the meth...

AI Technical Summary

Problems solved by technology

However, at present, the energy entropy of the entire signal is usually selected as the flutter feature, and the flutter frequency band and flutter feature vector are not really extracted.

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