Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor

Bing Li; Lichang Gu; Yubin Lin; Zhexiang Zou; Siqin Pang; Kaibo Lu; Guojin Feng; Fengshou Gu; Andrew D. Ball

doi:10.1007/978-3-030-75793-9_84

Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor

Bing Li, Lichang Gu, Yubin Lin, Zhexiang Zou, Siqin Pang, Kaibo Lu, Guojin Feng, Fengshou Gu, Andrew D. Ball

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

1 Citation (Scopus)

Abstract

To achieve high productivity and precision of machining shaft-like workpieces, many methods have been developed for in-process monitoring. This paper presents a novel monitoring method based on On-Rotor Sensing (ORS) techniques. Main vibration mechanisms of turning a shaft on a lathe were studied analytically, which shows great changes in vibration modes with turning operations. Experimental studies are then performed to identify the informative vibration features for monitoring and on-line diagnostics. The results show that the vibration perceived by ORS approach contains rich information for in-process monitoring. In particular, vibration characteristics in the frequency domain can sensitively distinguish between different depths of cut, feed lengths and tool wear status, paving fundamentals for in-process quality control. In addition, it also allows instable cuts to be indicated at infant stages, providing feedbacks for cutting parameter tuning. Therefore, this novel ORS based monitoring method paves a genuine data aggregation approach for Internet of Things (IoT) enabled intelligent manufacturing.

Original language	English
Title of host publication	Proceedings of IncoME-V & CEPE Net-2020
Subtitle of host publication	Condition Monitoring, Plant Maintenance and Reliability
Editors	Dong Zhen, Dong Wang, Tianyang Wang, Hongjun Wang, Baoshan Huang, Jyoti K. Sinha, Andrew David Ball
Place of Publication	9783030757922
Publisher	Springer Nature Switzerland AG
Pages	910-922
Number of pages	13
Volume	105
Edition	1st
ISBN (Electronic)	9783030757939
DOIs	https://doi.org/10.1007/978-3-030-75793-9_84
Publication status	Published - 16 May 2021
Event	5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network - Zhuhai, China Duration: 23 Oct 2020 → 25 Oct 2020 Conference number: 5 https://link.springer.com/book/10.1007/978-3-030-75793-9#about

Publication series

Name	Mechanisms and Machine Science
Volume	105
ISSN (Print)	2211-0984
ISSN (Electronic)	2211-0992

Conference

Conference	5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network
Abbreviated title	IncoME-V and CEPE Net-2020
Country/Territory	China
City	Zhuhai
Period	23/10/20 → 25/10/20
Internet address	https://link.springer.com/book/10.1007/978-3-030-75793-9#about

UN SDGs

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

SDG 9 Industry, Innovation, and Infrastructure

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Li, B., Gu, L., Lin, Y., Zou, Z., Pang, S., Lu, K., Feng, G., Gu, F., & Ball, A. D. (2021). Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor. In D. Zhen, D. Wang, T. Wang, H. Wang, B. Huang, J. K. Sinha, & A. D. Ball (Eds.), Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability (1st ed., Vol. 105, pp. 910-922). (Mechanisms and Machine Science; Vol. 105). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-75793-9_84

Li, Bing ; Gu, Lichang ; Lin, Yubin et al. / Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor. Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. editor / Dong Zhen ; Dong Wang ; Tianyang Wang ; Hongjun Wang ; Baoshan Huang ; Jyoti K. Sinha ; Andrew David Ball. Vol. 105 1st. ed. 9783030757922 : Springer Nature Switzerland AG, 2021. pp. 910-922 (Mechanisms and Machine Science).

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title = "Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor",

abstract = "To achieve high productivity and precision of machining shaft-like workpieces, many methods have been developed for in-process monitoring. This paper presents a novel monitoring method based on On-Rotor Sensing (ORS) techniques. Main vibration mechanisms of turning a shaft on a lathe were studied analytically, which shows great changes in vibration modes with turning operations. Experimental studies are then performed to identify the informative vibration features for monitoring and on-line diagnostics. The results show that the vibration perceived by ORS approach contains rich information for in-process monitoring. In particular, vibration characteristics in the frequency domain can sensitively distinguish between different depths of cut, feed lengths and tool wear status, paving fundamentals for in-process quality control. In addition, it also allows instable cuts to be indicated at infant stages, providing feedbacks for cutting parameter tuning. Therefore, this novel ORS based monitoring method paves a genuine data aggregation approach for Internet of Things (IoT) enabled intelligent manufacturing.",

keywords = "In-process monitoring, Intelligent manufacturing, Metal cutting, On-rotor sensing, Workpiece vibration",

author = "Bing Li and Lichang Gu and Yubin Lin and Zhexiang Zou and Siqin Pang and Kaibo Lu and Guojin Feng and Fengshou Gu and Ball, \{Andrew D.\}",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network, IncoME-V and CEPE Net-2020 ; Conference date: 23-10-2020 Through 25-10-2020",

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doi = "10.1007/978-3-030-75793-9\_84",

language = "English",

volume = "105",

series = "Mechanisms and Machine Science",

publisher = "Springer Nature Switzerland AG",

pages = "910--922",

editor = "Dong Zhen and Dong Wang and Tianyang Wang and Hongjun Wang and Baoshan Huang and Sinha, \{Jyoti K.\} and Ball, \{Andrew David\}",

booktitle = "Proceedings of IncoME-V \& CEPE Net-2020",

address = "Switzerland",

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Li, B, Gu, L, Lin, Y, Zou, Z, Pang, S, Lu, K, Feng, G, Gu, F & Ball, AD 2021, Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor. in D Zhen, D Wang, T Wang, H Wang, B Huang, JK Sinha & AD Ball (eds), Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. 1st edn, vol. 105, Mechanisms and Machine Science, vol. 105, Springer Nature Switzerland AG, 9783030757922, pp. 910-922, 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network, Zhuhai, China, 23/10/20. https://doi.org/10.1007/978-3-030-75793-9_84

Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor. / Li, Bing; Gu, Lichang; Lin, Yubin et al.
Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. ed. / Dong Zhen; Dong Wang; Tianyang Wang; Hongjun Wang; Baoshan Huang; Jyoti K. Sinha; Andrew David Ball. Vol. 105 1st. ed. 9783030757922: Springer Nature Switzerland AG, 2021. p. 910-922 (Mechanisms and Machine Science; Vol. 105).

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

TY - GEN

T1 - Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor

AU - Li, Bing

AU - Gu, Lichang

AU - Lin, Yubin

AU - Zou, Zhexiang

AU - Pang, Siqin

AU - Lu, Kaibo

AU - Feng, Guojin

AU - Gu, Fengshou

AU - Ball, Andrew D.

N1 - Conference code: 5

PY - 2021/5/16

Y1 - 2021/5/16

N2 - To achieve high productivity and precision of machining shaft-like workpieces, many methods have been developed for in-process monitoring. This paper presents a novel monitoring method based on On-Rotor Sensing (ORS) techniques. Main vibration mechanisms of turning a shaft on a lathe were studied analytically, which shows great changes in vibration modes with turning operations. Experimental studies are then performed to identify the informative vibration features for monitoring and on-line diagnostics. The results show that the vibration perceived by ORS approach contains rich information for in-process monitoring. In particular, vibration characteristics in the frequency domain can sensitively distinguish between different depths of cut, feed lengths and tool wear status, paving fundamentals for in-process quality control. In addition, it also allows instable cuts to be indicated at infant stages, providing feedbacks for cutting parameter tuning. Therefore, this novel ORS based monitoring method paves a genuine data aggregation approach for Internet of Things (IoT) enabled intelligent manufacturing.

AB - To achieve high productivity and precision of machining shaft-like workpieces, many methods have been developed for in-process monitoring. This paper presents a novel monitoring method based on On-Rotor Sensing (ORS) techniques. Main vibration mechanisms of turning a shaft on a lathe were studied analytically, which shows great changes in vibration modes with turning operations. Experimental studies are then performed to identify the informative vibration features for monitoring and on-line diagnostics. The results show that the vibration perceived by ORS approach contains rich information for in-process monitoring. In particular, vibration characteristics in the frequency domain can sensitively distinguish between different depths of cut, feed lengths and tool wear status, paving fundamentals for in-process quality control. In addition, it also allows instable cuts to be indicated at infant stages, providing feedbacks for cutting parameter tuning. Therefore, this novel ORS based monitoring method paves a genuine data aggregation approach for Internet of Things (IoT) enabled intelligent manufacturing.

KW - In-process monitoring

KW - Intelligent manufacturing

KW - Metal cutting

KW - On-rotor sensing

KW - Workpiece vibration

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UR - https://www.springer.com/gb/book/9783030757922

U2 - 10.1007/978-3-030-75793-9_84

DO - 10.1007/978-3-030-75793-9_84

M3 - Conference contribution

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VL - 105

T3 - Mechanisms and Machine Science

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EP - 922

BT - Proceedings of IncoME-V & CEPE Net-2020

A2 - Zhen, Dong

A2 - Wang, Dong

A2 - Wang, Tianyang

A2 - Wang, Hongjun

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A2 - Sinha, Jyoti K.

A2 - Ball, Andrew David

PB - Springer Nature Switzerland AG

CY - 9783030757922

T2 - 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network

Y2 - 23 October 2020 through 25 October 2020

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Li B, Gu L, Lin Y, Zou Z, Pang S, Lu K et al. Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor. In Zhen D, Wang D, Wang T, Wang H, Huang B, Sinha JK, Ball AD, editors, Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. 1st ed. Vol. 105. 9783030757922: Springer Nature Switzerland AG. 2021. p. 910-922. (Mechanisms and Machine Science). Epub 2021 May 16. doi: 10.1007/978-3-030-75793-9_84

Vibration Monitoring of Turning a Shaft on a Lathe Based on Signals from an On-Rotor Sensor

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