Online Monitoring of a Shaft Turning Process based on Vibration Signals from On-Rotor Sensor

Chun Li, Bing Li, Lichang Gu, Guojin Feng, Fengshou Gu, Andrew D. Ball

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

1 Citation (Scopus)

Abstract

To realize online monitoring of workpieces in the machining processes with universal lathes, this paper presents a novel vibration method based on a new On-Rotor Sensor (ORS) technology. The dynamic responses of a turning process were firstly examined by finite element analysis (FEA) and impact test analysis to gain a basic understanding of the vibration characteristics measured by ORS when the workpiece is under stationary states with both fixed-pinned and fixed-free boundaries. Experimental evaluations were then conducted under different depths of cut (DOC) for workpieces turning under both the pinned and free conditions. It has been shown that vibration responses are predominated by a low-frequency mode around 500 Hz and a high mode around 1200Hz, which corresponds to the first two lateral modes of the workpiece. The root mean squared (RMS) values filtered in these two bands allow turning processes with different DOCs and workpiece diameters to be differentiated. Besides, unstable turnings can also be detected by the standard deviation of RMS. These results show the proposed method is very promising for online real-time assessment of manufacturing quality, paving fundamentals for intelligent manufacturing.

Original languageEnglish
Title of host publicationProceedings - 2020 3rd World Conference on Mechanical Engineering and Intelligent Manufacturing, WCMEIM 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages402-407
Number of pages6
ISBN (Electronic)9781665441094
ISBN (Print)9781665431125
DOIs
Publication statusPublished - 4 Dec 2020
Event3rd World Conference on Mechanical Engineering and Intelligent Manufacturing - Virtual, Shanghai, China
Duration: 4 Dec 20206 Dec 2020
Conference number: 3

Conference

Conference3rd World Conference on Mechanical Engineering and Intelligent Manufacturing
Abbreviated titleWCMEIM 2020
CountryChina
CityVirtual, Shanghai
Period4/12/206/12/20

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