摘要
为了及时检测出急剧磨损的铣刀,提高加工效率,保证工件精度和表面质量,设计了一种基于机床主轴弯矩与扭矩信号的铣刀磨损状态监测方法,利用主轴上的扭矩和弯矩传感器对加工过程中的刀具进行实时在线测量,并对采集到的数据进行处理。试验结果表明,将切削力信号融合提取特征作为输入信号,可以提高刀具磨损状态识别的准确性,能够直接和准确地反映刀具磨损状态。
In order to detect sharply worn milling tools in time,improve processing efficiency,and ensure the accuracy and surface quality of the workpiece,a new method for monitoring the wear status of milling cutters based on the bending moment and torque signals of the machine tool spindle are designed.The sensor of the bending moment and torque signals measures the tools in the machining process online from time to time,and processes the collected data.The experimental results show that the cutting force signal fusion extraction feature as input can improve the accuracy of tool wear status recognition,and can directly and ccurately reflect the tool wear status.
作者
王亮
韩雷
密启欣
潘勇强
崔鸿宇
Wang Liang;Han Lei;Mi Qixin;Pan Yongqiang;Cui Hongyu(Chengdu Aeronautic Polytechnic,Chengdu 610100,China;不详)
出处
《工具技术》
北大核心
2022年第12期152-155,共4页
Tool Engineering
基金
成都航空职业技术学院自然科研项目(06221036)。
关键词
刀具状态监测
刀具磨损
弯扭力学信号
tool condition monitoring
tool wear
multi-feature signals
