Tool wear prediction in turning using workpiece surface profile images and deep learning neural networks

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...

Full description

Bibliographic Details
Main Authors: Lim, Meng Lip, Mohd Naqib, Derani, Ratnam, Mani Maran, Ahmad Razlan, Yusoff
Format: Article
Language:English
English
Published: Springer Science and Business Media Deutschland GmbH 2022
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/42653/
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

Similar Items

Similar Items