The accurate knowledge of High-speed motorized spindle dynamic behavior during machining is important in order to ensure the reliability of machine tools in service and the quality of machined parts. More specifically, the prediction of stable cutting regions, which is a critical requirement for high-speed milling operations, requires accurate estimation of tool/holder/spindle set dynamic modal parameters. These estimations are generally obtained through the Frequency Response Function (FRF) measurements of the non-rotating spindle. However, significant changes in modal parameters are expected to change during operation due to spindle high-speed rotation. The spindle modal variations are highlighted through an integrated dynamic high-speed spindle-bearing system finite element model taking into account rotor dynamics effects. The dependency of dynamic behavior on speed range is then investigated and determined with accuracy. The objective of the proposed paper is to validate these numerical results through an experimental-based approach. Hence, an experimental set up is elaborated to measure the rotating tool vibration during machining operation in order to measure the spindle modal frequencies variation with respect to spindle speed in an industrial environment. The identification of spindle natural frequencies under rotating condition is challenging due to the low number of sensors and the presence of many harmonics in the measured signals. In order to overcome the mentioned issues and to extract characteristics of the system, the spindle modes are determined through a 3 step procedure. First, spindle modes are highlighted using the Frequency Domain Decomposition (FDD) technique with a new formulation at the considered rotating speed. These identified modes are then analyzed through the value of their respective damping ratio in order to separate harmonics component from structural spindle natural frequencies. Finally, the stochastic properties of the modes are also investigated by considering the probability density of the retained modes. Results show a good correlation between numerical and experimental- based identified frequencies. The spindle-tool identified modal properties during machining allow considering the numeric model to be well representative of real dynamic effects during machining. Using this model, a new stability lobe diagram is proposed. By integrating the predicted model in the chatter vibration stability law, which indicates whether the design would lead to a chatter vibration-free cutting operation, accurate spindle cutting conditions can be predicted.
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