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。
Taking off-line control test for example, the reliability of cutting tool condition identification of this monitoring system has been assessed.
并以离线控制试验为实例，考核该系统识别刀具状态的可靠性。
In order to improve cutting tool condition monitoring, a method of cutting tool fault diagnosis based on wavelet and artificial networks with relaxed structure is proposed in this paper.
为了有效的进行刀具状态监测，采用小波神经网络的松散型结合对刀具进行故障诊断。
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。
Through collecting vibration signal and analyzing it in the frequency domain in the condition of changing parameter cutting, a single self power spectrum is hard to detect tool breakage effectively.
在变切削参数的加工工况下，通过对振动信号的采集和频域处理，发现采用单一的自功率谱方法难以有效检测出刀片破损。
Among the various way to monitor the condition of cutting tool, the way through Acoustic Emission (AE) is a most promising method.
在对刀具切削状态进行监测的众多方法中，声发射方法是一种最有前途的方法。
Enlarging the clearance of gear shaping cutter can improve efficiently its cutting condition, the gear surface quality and tool life.
加大插齿刀后角可以有效改善插齿刀的切削条件，提高齿表面加工质量和延长刀具使用寿命。
Based on acoustic emission, power monitoring and improved neural network technology and using cutting tool monitoring software, the normal or abnormal condition of cutting tools can be identified.
以声发射、功率监控和改进的神经网络技术，借助刀具监控软件，识别刀具切削工作的正常和失效状态。
Experiments indicate that this method has a high ratio of recognition in a range of cutting condition and even can detect novel tool faults.
实验结果表明，该方法不仅可以在多种切削条件下获得较高的识别率，还可以识别出新的刀具故障。
Experiments were implemented to obtain the motor power and AE signals under different cutting parameter condition(cutting velocity, feed velocity and cutting depth), tool wear and breakage conditions.
采用机床主电动机功率法和声发射（AE）法来获取切削过程中发出的刀具磨损和破损信号，建立了刀具状态试验系统。
One is the current signal model with bore cutting condition, and the another is the model of tool wear with cutting conditions and time.
第一种是基于电流信号的刀具磨损模型，第二种是直接基于刀具磨损量的模型，这两种模型均滤除了切削条件的影响。
This paper proposes that the total rigidity of a machine tool can be calculated in terms of the typical cutting condition at the beginning of design for the CNC lathe.
提出可根据数控车床设计时选用的典型切削条件来计算机床总刚度。
This paper proposes that the total rigidity of a machine tool can be calculated in terms of the typical cutting condition at the beginning of design for the CNC lathe.
提出可根据数控车床设计时选用的典型切削条件来计算机床总刚度。
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