Abstract
To achieve high-quality in-situ machining of large thin-walled workpieces, the dual-robot mirror milling technology has attracted much attention due to its ability to synchronously provide mirror support on the opposite side of the milling area of the tool. However, mirror support has a complex and unclear dynamics mechanism for improving the dynamic characteristics of workpieces, and strongly affects the stability of the machining process. Therefore, this paper proposes a time-varying dynamic characteristics and chatter prediction method for mirror milling based on support mechanism analysis and support parameter modeling. Firstly, by clarifying the dynamics mechanism between the pneumatic support head and the workpiece, the contact interface is equivalent to a spring-damper model with stiffness and damping (also known as support parameters). Meanwhile, a coupled time-varying dynamics model of the workpiece-support head system is established by adopting the Rayleigh-Ritz method. Then, the frequency response function (FRF) of the workpiece with the support head is derived to reveal the effect of pneumatic support on the dynamic characteristics of the workpiece. On this basis, a mechanism-based and data-driven identification and modeling method for support parameters and cylinder damping is proposed to improve the accuracy and applicability of dynamics models. Combined with the proposed end milling chatter model, the stability of the mirror milling system is predicted to reasonably select chatter-free process parameters. Finally, through a series of single- and multi-point support impact tests, the surrogate models of the support parameters and cylinder damping are established, and their validity and applicability are verified by experimental and predicted FRFs. Mirror milling experiments verify the effectiveness of the developed dynamics model and evaluate the feasibility of the mirror support strategy in suppressing chatter.
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