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 proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationProceedings of IncoME-V & CEPE Net-2020
Subtitle of host publicationCondition Monitoring, Plant Maintenance and Reliability
EditorsDong Zhen, Dong Wang, Tianyang Wang, Hongjun Wang, Baoshan Huang, Jyoti K. Sinha, Andrew David Ball
Place of Publication9783030757922
PublisherSpringer Nature Switzerland AG
Pages910-922
Number of pages13
Volume105
Edition1st
ISBN (Electronic)9783030757939
DOIs
Publication statusPublished - 16 May 2021
Event5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network - Zhuhai, China
Duration: 23 Oct 202025 Oct 2020
Conference number: 5
https://link.springer.com/book/10.1007/978-3-030-75793-9#about

Publication series

NameMechanisms and Machine Science
Volume105
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992

Conference

Conference5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network
Abbreviated titleIncoME-V and CEPE Net-2020
CountryChina
CityZhuhai
Period23/10/2025/10/20
Internet address

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