一种智能体的数控系统加工轨迹特征识别方法

Recognition of Agent Machining Trajectory Features in Numerical Control System

数控系统作为智能制造体系的关键组成部分,其性能直接影响着制造质量和整体生产效率.然而,现有的数控系统程序资源在特征识别方面的能力却相对有限,无法满足智能制造系统对于加工路径的感知能力以及对加工精度的需求,制约了数控系统在复杂、高速的加工场景中的性能表现.针对这一问题,提出了一种智能体的数控系统加工轨迹特征识别方法.采用智能体方法构建模型,分析数控工件加工生成的路径G代码的关键几何信息,构建特征库,结合深度学习技术对轨迹特征进了行高效的识别和分类.所设计的模型有助于实现数控系统对加工过程的感知与控制,以提高数控系统对复杂零件的感知能力,从而提升数控系统的可靠性.

As a key component of the intelligent manufacturing system,the performance of the CNC system directly affects the manufacturing quality and overall production efficiency.However,the ability of the existing numerical control system program resources in feature recognition is relatively limited,which cannot meet the perception ability of the intelligent manufacturing system for the processing path and the demand for machining accuracy,which restricts the performance of the numerical control system in complex and high-speed processing scenarios.In order to solve this problem,a method for identifying the machining trajectory features of the numerical control system of the agent was proposed.The agent method is used to construct the model,the key geometric information of the path G code generated by CNC workpiece processing is analyzed,the feature database is constructed,and the trajectory features are efficiently identified and classified by deep learning technology.The designed model helps to realize the perception and control of the machining process by the CNC system,so as to improve the perception ability of the CNC system on complex parts,so as to improve the reliability of the CNC system.