Premature detection of surface disruption – deep learning-based method for classification of damage on ball screw drives

被引：0
|
作者：
Schlagenhauf, Tobias [1 ]
Ruppelt, Peter [1 ]
Fleischer, J. [1 ]
机构：
[1] wbk – Institut für Produktionstechnik, Karlsruher Institut für Technologie (KIT), Kaiserstr. 12, Karlsruhe,76131, Germany
来源：
WT Werkstattstechnik | 2020年 / 110卷 / 7-8期
关键词：
Condition monitoring - Deep learning - Machine components - Machine tools - Preventive maintenance;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Condition monitoring of plants, machines and their components is a central topic of Industry 4.0. Unforeseeable failures of machine tools are often caused by wear, resulting in failure of ball screws and subsequent surface disruptions. This article describes how image-based monitoring of ball screws by an electronic camera system in combination with deep learningbased models enable the early detection of surface disruptions and to derive appropriate and preventive maintenance measures. © 2020, VDI Fachmedien GmBbH & Co. All rights reserved.
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页码：501 / 506
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