On-line chatter detection and control in boring based on an electrorheological fluid

Abstract For on-line chatter avoidance in boring, this paper presents an adaptive control system which, based on a novel design of the boring bar containing an Electrorheological (ER) fluid, automatically adjusts the dynamics of the bar according to the information from the monitored sensor signal. For detecting chatter rapidly and accurately, artificial neural networks are used to decontaminate the sensor signal and recognize the chatter omen. Once chatter is detected, a strength regulation strategy of the electric field applied to the ER fluid in the bar is used to suppress chatter. When a certain electric field is applied to the ER fluid in the bar it behaves as a viscoelastic spring with nonlinear vibration characteristics. Based on the nonlinear vibration characteristics of the ER fluid, the strength regulation strategy is to tune the electric field strength so that the dynamics of the bar is sensitive to the minute change of the vibration amplitude. Experiments show that chatter in boring can be avoided by using this control system.