系统辨识的刀具磨损特征量提取方法

Cutting tool wear feature extraction based on process identification

针对刀具磨损智能监控系统中信号预处理和磨损特征提取技术进行研究，提出了基于加工过程自适应模型参数估计的刀具磨损特征量提取方法，通过检测加工状态信号和加工参数，利用切削力模型和最小二乘法实现模型自动跟踪加工过程特性变化，并从估计的模型参数中获取刀具磨损特征量。经实验证明，加工过程切削力模型参数的变化能灵敏地反映刀具磨损特征，且该特征提取不受切削条件变化的影响。

Propose a strategy to obtain cutting tool wear feature, which is based on a process model and parameter estimation method. The adaptive model traces the properties of cutting process by combining process state signal, cutting conditions, force model and least square method. The tool wear feature is obtained from the estimated parameter of the model. Experiment results have proved that changes of the parameter of cutting force model significantly indicate tool wear independent of the varying of cutting conditions.