APPLICATION OF CLOUD-BASED MACHINE LEARNING IN CUTTING TOOL CONDITION MONITORING

IF 4 Q2 ENGINEERING, INDUSTRIAL
M. Milošević, D. Lukić, G. Ostojić, M. Lazarević, A. Antić
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引用次数: 0

Abstract

One of the primary technologies in the Industry 4.0 concept refers to Smart maintenance or predictive maintenance that includes continuous or periodic sensor monitoring of physical changes in the condition of manufacturing resources (Condition monitoring). In this way, production delays or failures are timely prevented or minimized. In this context, the paper present a developed cloud-based system for monitoring the condition of cutting tool wear by measuring vibration. This system applies a machine learning method that is integrated within the MS Azure cloud system. The verification was performed on the data of the calculated central moments during the turning process, for cutting tool inserts with different degrees of wear.
基于云的机器学习在刀具状态监测中的应用
工业4.0概念中的主要技术之一是智能维护或预测性维护,包括对制造资源状态的物理变化进行连续或定期的传感器监测(状态监测)。通过这种方式,及时防止或最小化生产延迟或故障。在此背景下,本文开发了一种基于云的系统,通过测量振动来监测刀具磨损状况。该系统应用了集成在MS Azure云系统中的机器学习方法。针对不同磨损程度的刀具刀片,对车削过程中计算的中心力矩数据进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.50
自引率
6.70%
发文量
21
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