Online Chatter Detection and Suppression System for Intelligent Machine Tool

Abstract

In machining processes, chatter, as an unstable phenomenon, has been a major problem due to its adverse effects on productivity, surface finish and machine tool components. It is of great importance to avoid chatter and ensure the stable turning process. A real-time chatter detection and suppression system (CDSS) to avoid chatter in turning processes is presented. The weighted wavelet packet entropy is employed to monitor the turning process and it detects chatter in the premature stage. Once chatter is identified, the dominant chatter frequency is immediately estimated by the scale factor-based interpolated DFT. The spindle speed variation, which periodically modulates the spindle speed around a nominal value, is instantly activated to suppress chatter. The variation parameters, i.e. amplitude and frequency, are computed based on dominant chatter frequency. In this way, chatter can be automatically identified and suppressed in an online fashion before it has fully developed. To experimentally verify the proposed method, the end-face turning of a flexible disc is carried out on a numerical control lathe with Siemens 840D. Two turning experiments with and without the CDSS are conducted using the same cutting parameters, cutting tool and workpiece. Experimental results demonstrate that chatter can be automatically detected and suppressed by the CDSS before chatter arrives at fully developed stage.