Acoustic emission (AE) is a new method for cutting tool condition monitoring.
声发射是一种新的切削刀具状态的监测方法。
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。
This paper proposes a composite neural model for tool condition monitoring. It is composed with several neural networks and the number of neural networks is equal to the number of tool faults.
提出了一种用于刀具状态监测的复合神经网络模型，模型由多个神经网络组成，神经网络的数目等于要监测的刀具故障数目。
Tool condition monitoring is the key technique in automatic and unmanned machining process.
刀具状态监测是实现自动化加工和无人化加工的关键技术。
Tool condition monitoring is the key technique in automatic and unmanned machining process.
刀具状态监测是实现自动化加工和无人化加工的关键技术。
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