Intelligent monitoring of tool wear based on machine internal data

被引：0
|
作者：
Brecher C. [1 ]
Xi T. [1 ]
Benincá I.M. [1 ]
Kehne S. [1 ]
Fey M. [1 ]
机构：
[1] Werkzeugmaschinenlabor (WZL) der RWTH Aachen, Steinbachstr. 19, Aachen
来源：
WT Werkstattstechnik | 2021年 / 111卷 / 05期
关键词：
Learning systems;
D O I：
10.37544/1436-4980-2021-05-43
中图分类号：
TG [金属学与金属工艺]; TH [机械、仪表工业];
学科分类号：
0802 ; 0805 ;
摘要：
Numerical controls for machine tools acquire a considerable amount of sensor data for axis control. This information, such as the current axis position or the motor currents, can be used for monitoring other process variables with the aid of models. This article investigates a machine learning method for monitoring tool wear in machine tools, based on machine-internal data only. © 2021, VDI Fachmedien GmBbH & Co.. All rights reserved.
引用
收藏
页码：309 / 313
页数：4
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