异形螺杆数控铣削刀具磨损智能建模研究

Research on tool wear Intelligent modeling of special spiral rod numerical control milling

介绍了一种在线估算螺杆数控铣削中刀具磨损量的新方法。该方法基于螺杆铣削过程变切削参数的工况,提取了振动信号和功率信号的刀具磨损特征值,基于自适应神经—模糊推理系统建立了刀具磨损数学模型。实验证明,由此建立的刀具磨损模型能够排除切削参数变化的干扰,可以较好的反映加工中刀具磨损状态,同时也为具有时变切削参数特性的加工过程刀具磨损状态监控提供了新的研究方法。

New method for online tool wear estimation in spiral rod numerical controlled milling is presented. Firstly the variable cutting parameters of spiral rod milling are analyzed to extract the eigenvalue of vibration and power signals. Then the tool wear mathematical model is built up based on adaptive neuro - fuzzy inference system. Experimental results have proved the effectiveness of the method proposed to reflect the actual tool condition during the milling process in spite of the varying cutting parameters. Moreover, it provides a new approach for tool wear condition monitoring of other milling processes with time - varying cutting parameters.