Study on Tool Wear State Monitoring of Variable Parameters Milling
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摘要: 针对切削力旧有时域特征易受切削参数变动影响而不适用于变参数铣削刀具磨损状态监测的缺陷,采用了一组新的无量纲切削力时域特征(归一化切削力指标NCF、变异系数Cv和峰值力比MFR)。并以难加工材料TC4钛合金变参数铣削实验来验证新特征在变参数铣削刀具磨损状态监测上的有效性,分别以新旧特征作为SVM分类器的输入,分析和比较结果表明本文提出的无量纲切削力时域特征对切削参数变化不敏感,而仅对刀具磨损状态变化敏感,因此能够实现变参数铣削刀具磨损状态监测。Abstract: The old time domain features from the cutting force are vulnerable to changes of cutting parameters. So it is not suitable for tool wear monitoring under variable parameters. In order to solve the above mentioned problem, a new set of dimensionless time domain feature including normalized cutting force indicator NCF, variation coefficient Cv and peak force ratio MFR are adopted. To verify the effectiveness of the present feature for tool wear monitoring under variable parameters, the end milling experiment of TC4 titanium alloy was designed. Then, the present features and the old features are input Support Vector Machines (SVM) to monitor the tool wear state respectively. The analysis and comparison results show that the dimensionless time domain feature presented in the paper is not sensitive to the cutting parameters, but only sensitive to the tool wear state. Hence, the tool wear state monitoring under variable parameters can be implemented.
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Key words:
- tool wear state /
- variable parameters /
- monitoring
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