主轴运行状态下机床刀尖点动力学行为分异特征辨识

刀尖点动力学特性直接影响切削稳定性和加工表面的质量。现阶段对主轴运行状态下刀尖点动力学特性的理论研究和实验研究分别存在着建模复杂和设备昂贵等局限性。为此，提出一种基于半理论法的主轴运行状态下刀尖点动力学行为分异特征辨识方法。该方法将分异特征辨识转化为一类优化设计问题，即以不同转速下刀尖点动力学特性参数为变量、以极限切深和颤振频率的实验标定值与理论预测值的偏差之和最小为目标构建优化模型，并借助粒子群退火优化算法进行求解，从而获得在不同转速下刀尖点动力学行为的分异特征及规律。以某型立式加工中心为平台，通过变切深铣削实验，对所提出的辨识方法进行验证，结果显示极限切深预测值与标定值吻合度较高。在不需复杂建模和昂贵实验设备的条件下，利用所提出的方法能够准确预测运行状态下刀尖点动力学行为分异特征，实现切削稳定性的精准预测，为进一步提高铣削加工质量和效率提供理论基础和数据支撑。

Identification of dynamics behavior differentiation characteristics of machine tool tip under spindle running operation

The dynamics characteristics of tool tip directly affect the cutting stability and the quality of machined surface. At present, the theoretical research and experimental research on the dynamics characteristics of tool tip under the spindle running state have some limitations, such as complex modeling and expensive equipment. Therefore, the identification method of dynamics behavior differentiation characteristics of tool tip under spindle running operation based on semi-theoretical method was proposed. In this method, the differentiation characteristic identification was transformed into a kind of optimization design problem, that was, taking the dynamics characteristic parameters of tool tip at different rotational speeds as variables, and taking the minimum summation of deviations of between the experimental calibration value and the theoretical prediction value of the limit cutting depth and flutter frequency as the objective, the optimization model was constructed and solved with the help of the particle swarm annealing optimization algorithm. Therefore, the dynamics behavior differentiation characteristics and laws of tool tip at different rotational speeds were obtained. Taking a vertical machining center as the platform, the proposed identification method was verified by variable cutting depth milling experiment. The results showed that the calibration value of limit cutting depth was in good agreement with the predicted value. Without complex modeling and expensive experimental equipment, the proposed method can accurately predict the dynamics behavior differentiation characteristics of tod tip, and can accurately predict the cutting stability, which can provide a theoretical basis and data support for further improving the milling quality and efficiency.