In-Process Detection of Tool Breakage in Milling

Abstract

An adaptive signal processing scheme for the cutting force signal was used to detect the fracture and chipping of a cutting tool during milling operation. The cutting force signal was modeled by a discrete autoregressive model where parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on a model reference adaptive system approach. The sensitivity of the prediction error and the estimated parameters to the frature and chipping of a cutting tool are presented. The influence of the adaptation algorithm parameters on the estimation results is discussed. The effect of the change in cutting conditions on the estimation results is also investigated.