基于特征融合的刀具磨损监测方法

A Tool Wear Monitoring Method Based on Feature Fusion

提出了一种基于特征融合的刀具磨损监测方法，将该方法应用于铣刀磨损监测取得了较好的效果，文中论述了特征融合方法的基本思想，多传感器信号的特征关联、抽取及正规化处理，作为融合中心的神经网络的构造及训练等内容。实验分析表明，该方法实现刀具磨损监测是行之有效的。

This paper presents a tool wear monitoring method based on feature fusion via neural networks. The basic principle of this method, feature association, featureextraction, data normalization and neural networks construction of the method are discussed. The experimintal results show that the proposed method for tool wear monitoring is reliable and effective.