Affiliation:
1. Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109
Abstract
A normalized chatter detection index, which is independent of cutting conditions, is critical for machining process monitoring and control. This paper introduces a novel method for on-line machine-tool chatter detection. The method characterizes the significant transition in the cutting dynamics at the onset of chatter by the changes in the instantaneous energy of the machining system. This technique utilizes the relation between the Teager–Kaiser nonlinear energy operator and time-frequency (Wigner) distribution to develop a normalized chatter detection index. The validity of this technique is demonstrated with the actual experimental cutting data obtained from turning and milling processes.
Subject
Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering
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