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

doi:10.23919/IConAC.2018.8748978

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 proceeding › Conference contribution › peer-review

2 Citations (Scopus)

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 language	English
Title of host publication	ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing
Subtitle of host publication	Improving Productivity through Automation and Computing
Editors	Xiandong Ma
Publisher	IEEE
ISBN (Electronic)	9781862203426
DOIs	https://doi.org/10.23919/IConAC.2018.8748978
Publication status	Published - Sept 2018
Event	24th IEEE International Conference on Automation and Computing, ICAC 2018 - Newcastle upon Tyne, United Kingdom Duration: 6 Sept 2018 → 7 Sept 2018

Publication series

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

Conference

Conference	24th IEEE International Conference on Automation and Computing, ICAC 2018
Country/Territory	United Kingdom
City	Newcastle upon Tyne
Period	6/09/18 → 7/09/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

NC machining
OPC
Spindle power
TCMS
Threshold calculation

Access to Document

10.23919/IConAC.2018.8748978

Cite this

Han, L., Zou, Y., Ding, G., Zhu, M., Jiang, L., Qin, S., & Liang, H. (2018). Development of an online tool condition monitoring system for nc machining based on spindle power signals. In X. Ma (Ed.), ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing Article 8748978 (ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing). IEEE. https://doi.org/10.23919/IConAC.2018.8748978

Han, Lei ; Zou, Yisheng ; Ding, Guofu et al. / Development of an online tool condition monitoring system for nc machining based on spindle power signals. ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing. editor / Xiandong Ma. IEEE, 2018. (ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing).

@inproceedings{71174788bda84d6d9b91feb44723f110,

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

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.",

keywords = "NC machining, OPC, Spindle power, TCMS, Threshold calculation",

author = "Lei Han and Yisheng Zou and Guofu Ding and Menghao Zhu and Lei Jiang and Shengfeng Qin and Hongqin Liang",

year = "2018",

month = sep,

doi = "10.23919/IConAC.2018.8748978",

language = "English",

series = "ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing",

publisher = "IEEE",

editor = "Xiandong Ma",

booktitle = "ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing",

address = "United States",

note = "24th IEEE International Conference on Automation and Computing, ICAC 2018 ; Conference date: 06-09-2018 Through 07-09-2018",

}

Han, L, Zou, Y, Ding, G, Zhu, M, Jiang, L, Qin, S & Liang, H 2018, Development of an online tool condition monitoring system for nc machining based on spindle power signals. in X Ma (ed.), ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing., 8748978, ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing, IEEE, 24th IEEE International Conference on Automation and Computing, ICAC 2018, Newcastle upon Tyne, United Kingdom, 6/09/18. https://doi.org/10.23919/IConAC.2018.8748978

Development of an online tool condition monitoring system for nc machining based on spindle power signals. / Han, Lei; Zou, Yisheng; Ding, Guofu et al.
ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing. ed. / Xiandong Ma. IEEE, 2018. 8748978 (ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Development of an online tool condition monitoring system for nc machining based on spindle power signals

AU - Han, Lei

AU - Zou, Yisheng

AU - Ding, Guofu

AU - Zhu, Menghao

AU - Jiang, Lei

AU - Qin, Shengfeng

AU - Liang, Hongqin

PY - 2018/9

Y1 - 2018/9

N2 - 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.

AB - 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.

KW - NC machining

KW - OPC

KW - Spindle power

KW - TCMS

KW - Threshold calculation

UR - https://www.scopus.com/pages/publications/85069159133

U2 - 10.23919/IConAC.2018.8748978

DO - 10.23919/IConAC.2018.8748978

M3 - Conference contribution

AN - SCOPUS:85069159133

T3 - ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing

BT - ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing

A2 - Ma, Xiandong

PB - IEEE

T2 - 24th IEEE International Conference on Automation and Computing, ICAC 2018

Y2 - 6 September 2018 through 7 September 2018

ER -

Han L, Zou Y, Ding G, Zhu M, Jiang L, Qin S et al. Development of an online tool condition monitoring system for nc machining based on spindle power signals. In Ma X, editor, ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing. IEEE. 2018. 8748978. (ICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing). doi: 10.23919/IConAC.2018.8748978

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

Abstract

Publication series

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UN SDGs

Keywords

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