Early chatter identification of robotic boring process using measured force of dynamometer

Abstract

The system of robotic boring, mainly involving an industrial robot and an end-effector, is prone to chatter during the boring process of intersection hole, which not only affects the machining surface quality, but also restricts the boring efficiency. To improve the quality and the efficiency of the intersection hole, a new approach to identify and forecast the chatter of a robotic boring system based on the measured force signal of the dynamometer is presented. The proposed approach consists of three steps. First, the measured force signal is decomposed a series of intrinsic mode functions (IMF) and a residue by empirical mode decomposition (EMD). Secondly, Hilbert transform is invoked for each IMF to obtain the instantaneous frequencies and the instantaneous magnitudes, which comprise the Hilbert-Huang spectrum of the original signal. Finally, the chatter feature is extracted by analyzing the Hilbert spectrum of each IMF and a statistical method is used to detect the chatter symptom. The experiment results show that the extracting chatter feature from the signal can gain the chatter symptom at most 0.6 s ahead of the chatter outbreak, which is beneficial to guarantee for follow-up chatter suppression and improve the surface quality of workpiece.