Abstract: Weakly rigid drilling systems such as robots are widely used in complex drilling scenarios because of their good flexibility and wide operating range.However,its weak rigidity would easily lead to flutter and burr.How to control burr is a hot and difficult point in the research.Based on digital twin technology,a weak rigid drilling system was proposed that consisted of entity model,virtual model,data processing module and drilling decision-making module.The behavior-rule model based on mechanism and data fusion was proposed to realize the state monitoring in the machining process.The proposed drilling decision-making module included a decision-information generation model andoptimization algorithms to make state optimization.The feasibility and effectiveness of the burr monitoring process and the decision-making process were verified by the comparison between the physical drilling experiment and the simulation experiment of the weak rigid machining system.The results showed that the average burr height could be reduced by about 14%.

Key words: weak rigidity, drilling, digital twins, decision optimization, burr control

摘要： 机器人等弱刚性钻削系统柔性好、作业范围大,在复杂钻削场景中得到了广泛应用。但其弱刚性易导致颤振并产生毛刺,如何控制毛刺是研究热点和难点。由此,提出一种基于数字孪生的弱刚性钻削毛刺控制系统,由实体模型、虚拟模型、数据处理模块和钻削决策模块4部分组成。该方法在数字空间中构建钻削机理和数据融合的行为规则模型,实现对实体模型钻削加工过程的实时状态监测;所构建的钻削决策模块包括面向毛刺控制的决策信息生成模型和局部优化算法,实现对钻削加工过程的实时优化调控。通过弱刚性加工系统的物理钻削实验以及信息空间仿真实验的交互对比,验证了毛刺监测过程和决策反馈过程的可行性和有效性,结果表明所提数字孪生系统可使毛刺平均高度降低约14%。

关键词: 弱刚性, 钻削, 数字孪生, 决策优化, 毛刺控制