Charoenprasit, S., Seemuang, N. and Slatter, T. orcid.org/0000-0002-0485-4615 (2018) Monitoring Tool Wear in Drilling Process Using Spindle Noise Features. International Journal of Mechanical Engineering and Robotics Research, 7 (5). pp. 564-568. ISSN 2278-0149
Abstract
The use of worn cutting tools has a detrimental effect on the surface finish of a workpiece, tool precision and internal machine stress. Worn tools also decrease productivity through unplanned stops, tool changes and increase the production of scrap material. This study investigates an inexpensive and non-intrusive method of inferring tool wear by measuring the audible sounds emitted during a drilling process. A microphone was used to record the machining operation sound of S50C steel, which was drilled using a computer numerical control (CNC) milling machine in wet conditions. The audio signature was examined using a spectrogram, and the extracted sound features of the rotating spindle motor in the frequency domain were used to correlate with tool wear. The results indicated that the frequency of spindle noise was unrelated to tool wear, but although the magnitude of spindle noise significantly increased in accordance with tool wear progression.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 International Journal of Mechanical Engineering and Robotics Research. |
Keywords: | tool wear monitoring; wear monitoring; drilling; spindle noise |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Sep 2018 13:09 |
Last Modified: | 17 Sep 2018 13:13 |
Published Version: | http://www.ijmerr.com/index.php?m=content&c=index&... |
Status: | Published |
Publisher: | International Journal of Mechanical Engineering and Robotics Research |
Refereed: | Yes |
Identification Number: | 10.18178/ijmerr.7.5.564-568 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:135680 |