Development of an online tool condition monitoring system for nc machining based on spindle power signals

Lei Han, Yisheng Zou, Guofu Ding, Menghao Zhu, Lei Jiang, Shengfeng Qin, Hongqin Liang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a new online Tool Condition Monitoring System (TCMS) based on Object Linking and Embedded (OLE) for Process Control (OPC) Automation Interface of Computer Numerical Control (CNC) system for shop floor applications. The developed TCMS is able to acquire, display and analyze the spindle power signals automatically from the Panel Control Unit (PCU) of a machine tool in real-time. Tool condition is remote monitored and automatically determined by using adaptive thresholds calculated through statistical method put forward. Experiments are carried out and verify the accuracy and utility of the developed system.

Original languageEnglish
Title of host publicationICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing
Subtitle of host publicationImproving Productivity through Automation and Computing
EditorsXiandong Ma
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781862203426
DOIs
Publication statusPublished - Sep 2018
Event24th IEEE International Conference on Automation and Computing, ICAC 2018 - Newcastle upon Tyne, United Kingdom
Duration: 6 Sep 20187 Sep 2018

Publication series

NameICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing

Conference

Conference24th IEEE International Conference on Automation and Computing, ICAC 2018
CountryUnited Kingdom
CityNewcastle upon Tyne
Period6/09/187/09/18

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