Abstract
In order to simulate the cutting performance of a spindle mounted in the machine tool, the finite element (FE) model of spindles is required to be coupled with machine tool. However, the unknown joint dynamics (e.g., bolts) between the spindle and machine tool column limit the accuracy of the model. In this paper, an FE model updating method is proposed based on the identification of joint dynamics in both translational and rotational degrees-of-freedom (DOF). The receptance coupling (RC) technique is enhanced to estimate frequency response functions (FRFs) corresponding to rotational DOFs. The joint stiffness is identified through the iteration process by minimizing the difference between the simulated FRF and the measured FRF of the assembly. The proposed method is verified with a machine-tool spindle system. The good agreement between simulation and experiment shows the effectiveness of the method.
Highlights
Apart from excessive tool wear/breakage, chatter is still the biggest obstacle in increasing material removal rates in highspeed machining
There is a critical need to develop a scientific and systematic tool that can assist industrial engineers in achieving a reliable finite element (FE) model which can accurately represent the dynamic characteristics of the machine-tool spindle system
Pradhan and Modak [26] proposed a method for damping matrix identification using frequency response data, and Wang et al [27] established a method of identifying joint dynamic properties using partially measured frequency response functions (FRFs)
Summary
Apart from excessive tool wear/breakage, chatter is still the biggest obstacle in increasing material removal rates in highspeed machining. The FRF-based model updating methods make use of the measured FRFs directly which circumvent the need to identify the modal parameters from the experiments [12,13,14,15,16,17] These methods are able to produce highly accurate updated system matrices through iteration. Pradhan and Modak [26] proposed a method for damping matrix identification using frequency response data, and Wang et al [27] established a method of identifying joint dynamic properties using partially measured FRF. The experimental results show that the updated model can represent the dynamic behavior of the spindle mounted in the machine-tool column fairly accurately when the dynamics of the joints are largely unknown.
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