Tool wear prediction in turning using workpiece surface profile images and deep learning neural networks
Accurate prediction of tool flank wear during turning is important so that the cutting tool can be replaced before excessive damage occurs to the workpiece surface. Existing online methods of tool wear prediction using sensor signals can be affected by noise, thus resulting in false alarms. The aim...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Springer Science and Business Media Deutschland GmbH
2022
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/42653/1/Tool%20wear%20prediction%20in%20turning%20using%20workpiece%20surface.pdf http://umpir.ump.edu.my/id/eprint/42653/2/Tool%20wear%20prediction%20in%20turning%20using%20workpiece%20surface%20profile%20images%20and%20deep%20learning%20neural%20networks_ABS.pdf http://umpir.ump.edu.my/id/eprint/42653/ https://doi.org/10.1007/s00170-022-09257-2 https://doi.org/10.1007/s00170-022-09257-2 |
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