Mode shape database-based estimation for machine tool dynamics

Abstract

The system dynamics of machine tools plays an important role in machine health monitoring and quality assessment of manufacturing products. For former identification methods, the system dynamics are achieved with premises that do not fit with the real cutting conditions, as experimental modal analysis is realized only in idle status, and operational modal analysis limits the excitation form for vibration. Meanwhile, the dynamics variation during the machining is viewed discretely with no proper handles for the changes caused by cutting position movements. In this study, a mode shape database-based TOMA (MSDB-TOMA) estimation method is proposed for the system dynamics of machine tools under variation caused by component movements. The establishment principle of a mode shape database for capturing dynamics variation influenced by movements of cutting positions is proposed, with good fitting performance proved in a finite element model (FEM) of a machine tool. After that, the performance of dynamics estimation with the proposed method is validated using matched mode shapes from the pre-built database. The estimation for system dynamics parameters, e.g., natural frequency, presents a maximum error of within 0.04%, which turns out to be precise when compared with the real value from modal analysis in simulation. The feasibility experiment on FEM for estimating dynamics variation with component movements indicates the possibility of in-process dynamics recognition for real machining using the proposed method.