Systems for automatic tool wear monitoring contribute to measures to reduce manufacturing costs considerably.
刀具磨损状态自动识别系统能够显著地降低制造成本。
The experiment result proves that this system can be applied to the real-time tool wear monitoring successfully.
实验结果证明该系统可成功应用于刀具磨损量的实时监测。
Therefore, the tool wear monitoring had important practical significance for high speed milling machining technology application.
因此，刀具磨损的监测对高速铣削加工技术的推广应用有重要的实际意义。
CNC tool wear monitoring has great importance in improving the utilization of machine tools and in reducing the economic losses due to the tool wear.
数控机床刀具磨损监测对于提高刀具利用率，减小因刀具磨损而造成的损失具有重要意义。
The on-line monitoring of tool wear and breakage is one of the basic functions of FMS.
刀具磨损、破损的在线监控是FMS的基本功能之一。
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。
After survey of tool wear status online monitoring, the paper gives a new way to monitor the tool wear status based on speech recognition.
分析了刀具在线监测研究概况，提出了基于语音识别技术的刀具工况在线监测方法。
Through the analysis of image characteristic of crater wear in kentanium tool front face, arithmetic monitoring wear is designed, correlative software is exploited.
通过对硬质合金刀具前刀面月牙洼磨损图像特征的分析，设计了检测磨损的算法，并开发了相关软件。
However, HSM tool wear fast and service life is short. "Cutter breakage" phenomenon easily appears if not for real-time monitoring.
但是，高速铣削刀具磨损快，使用寿命短，如不进行实时监测很容易出现“打刀”现象。
An analysis and research are made on the techniques of monitoring the tool wear state and its compensation in EDM milling. Compensating strategies for the tool wear are proposed.
对电火花铣削加工中电极损耗状态的获得及其补偿技术进行了分析研究，提出了电极损耗的各种补偿策略。
The phenomenon mechanism appeared has been explained in the paper, and a method of making use of these signal characteristics for monitoring and predicting tool wear states is put forward.
文中解释了这种现象发生的机理，并提出利用该特性进行钻头磨损监测和预报的方法。
The maximal error is 7.4% in terms of two-dimension characteristic monitoring tool wear and the method can meet the need of generic project by the example.
经过实例检验，根据二维特征检测刀具磨损的最大误差在7.4%之内，可满足一般工程要求。
The maximal error is 7.4% in terms of two-dimension characteristic monitoring tool wear and the method can meet the need of generic project by the example.
经过实例检验，根据二维特征检测刀具磨损的最大误差在7.4%之内，可满足一般工程要求。
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