变工况3维铣削稳定性预报方法研究

传统铣削稳定性预报大多仅针对切削宽度恒定的定工况,其结果并不适用于在切宽具有时变特征的变工况下指导选取无颤振铣削工艺参数。为此,以再生型铣削颤振机理为理论基础,通过推导基于时变径向切削宽度的刀齿切入/切出角,并综合考虑切削过程阻尼与刀尖点动力学行为非对称性,构建变工况二自由度铣削动力学模型；进而,在由转速、轴向切深、径向切宽所创成的变工况三维空间内,借助时域全离散方法对动力学模型稳定性进行判定,并绘制三维稳定性叶瓣曲面,从而形成一套针对变工况的三维铣削稳定性预报方法体系。以某型立式加工中心为平台,通过实施典型变工况铣削实验,对所提三维稳定性预报方法进行验证。数据对比分析表明,所提方法能较准确地预报变工况下稳定极限铣削工艺参数,与实测数据相比,其最大相对误差为5.9%。以该预报结果作为边界约束条件,有利于实现面向最大金属去除率的铣削工艺参数优化。

Research on the Methodology of 3D Milling Stability Prediction on Varying Cutting Conditions

The traditional milling stability prediction approaches mainly focused on the fixed cutting conditions where the radial cutting widths were constant. The derived outputs were then not appropriate for choosing the chatter free milling parameters on varying cutting conditions where the radial cutting widths were changeable versus time. Therefore in this paper, according to the mechanisms of regenerative chatter, a two degrees of freedom milling dynamic model is established by considering both process damping and asymmetric dynamic behaviors of tool center point, where the instantaneous engaging and exit angles caused by the time-varying radial cutting width is also introduced. Time-domain full discrete method is adopted to determine the stabilities of the milling dynamic model within the three dimensional space created by taking account of varying cutting conditions including rotary velocities, axial cutting depths, and radial cutting widths. Following the 3D stability lobe surface being plotted, the entire 3D milling stability prediction methodology can be finally organized. A vertical machining center is selected as the experimental platform on which the milling tests are performed on varying cutting conditions. According to the comparisons between calculated and measured results, the proposed methodology is verified to be capable of predicting the limit stable milling parameters accurately on varying cutting conditions, where the maximum relative error is found 5.9%. It is then beneficial to realize the maximum metal removal rate by optimizing the milling parameters subjecting to the predicted stability.