In-process tool point FRF identification under operational conditions using inverse stability solution

Self-excited vibrations of machine tools during cutting result in process instability, poor surface finish and reduced material removal rate. In order to obtain stability lobe diagrams to avoid chatter vibrations, tool point frequency response function (FRF) must be determined. In classical machine tool studies, tool point FRF is obtained experimentally or analytically for the idle state of the machine. However, during cutting operations, discrepancies are frequently observed between the stability diagrams predicted by using the FRFs measured at the idle state and the actual stability of the process. These deviations can be attributed to the changes in machine tool dynamics under cutting conditions which are difficult to measure. In this study, a new identification method is proposed for the identification of in-process tool point FRFs. In this method, experimentally determined chatter frequency and corresponding axial depth of cut are used in order to identify tool point FRF. The proposed method is applied to a real machining center and by using chatter tests it is demonstrated that the tool point FRF can be accurately identified under operational conditions.