Sensor-Based Chatter Detection and Avoidance by Spindle Speed Selection

Abstract

This paper presents the results of a series of experimental studies of a control system which, based on information from available sensors (in this case a microphone was primarily used), automatically adjusts the spindle speed and the feed rate so as to achieve stable milling. It is seen that by iteratively adjusting the spindle speed so that the frequency with which the teeth pass is equal to the dominant frequency in the spectrum of the sensor output, the system will very quickly be driven into a stable region, if such a stable region exists. Experimental results which confirm the applicability of this control scheme to a variety of milling operations are presented. They include slotting and partial immersion cuts in cast iron and aluminum. Since this strategy is based on information supplied by the sensors, it is capable of adapting to tool changes, thin webs, corners, etc… which cause changes in the dynamics of the machine-tool-workpiece system and therefore may cause chatter to arise during the course of a milling operation. This strategy does not require an a priori knowledge of the dynamics of the machine-tool-workpiece system as do most of the off-line methods.