The first kind of models can be used to on line identify the tool wear condition by using current signals.
对于第一种模型，可利用电流信号进行刀具磨损状态的在线识别；对于第二种模型，综合了时间因素的影响，可直接识别刀具磨损量。
This paper researches on the tool wear condition monitoring by cutting sound signal and workpiece surface texture based on analysis of the relative situation.
本论文在分析现状的基础上，从切削声信号和工件表面纹理这两个方面对刀具磨损状态监测技术进行了研究。
After a brief introduction the importance of tool condition monitoring, the paper derived the relationship between the spindle current and tool wear theoretically.
在简单介绍监测刀具状态的重要性的基础上，文章从理论上推导了主轴电流与刀具磨损量之间的关系式。
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