基于主轴功率的刀具在线监测系统

Tool On-Line Monitoring System Based on Spindle Power

刀具状态监测主要监测刀具过度磨损、断刀、崩刀等情况,在高速加工中具有重要意义。在刀具正常磨损过程中,刀具状态监测能够预测刀具的使用寿命,不仅可以提高刀具利用率,还可以节约成本。通过监测主轴电机电流信号间接识别出刀具的磨损状况,通过自学习建立刀具状态参考区间,并使用K-邻近算法利用样本数据计算出刀具寿命曲线,预测刀具的寿命情况。此外,通过与数控铣床(Computer Numerical Control,CNC)系统集成编写了一套完整的测试系统,并通过实际的机床进行了测试,展示了一个低成本、易于实现的刀具在线监控系统。

Tool condition monitoring, including excessive tool wear and tool breakage has great significance in high speed machining.During normal tool wear,the tool life predicted Function can not only improve tool utilization rate but also save cost.In this paper, the tool wear condition is recognized indirectly by the current signal of spindle motor, and the tool state reference interval is established by self-learning method, also the K-adjacency algorithm is used to calculate the tool life curve from sample data.In addition,by integrating with the CNC system, a set of testing system was written and tested by the actual machine.Therefore, this paper shows a low-cost, easy to implement tool online monitoring system.