TY  - GEN 
AU  - García Ordás, María Teresa
AU  - Alegre Gutiérrez, Enrique
AU  - Alaiz Rodríguez, Rocío
AU  - González Castro, Víctor
A4  - Ingenieria de Sistemas y Automatica
DA  - 2018/04/04
SN  - 0888-3270
UR  - https://hdl.handle.net/10612/17635
AB  - [EN] In this work we propose a new online, low cost and fast approach based
on computer vision and machine learning to determine whether cutting tools
used in edge pro le milling processes are serviceable or disposable based on
their wear level. We...
LA  - eng
PB  - Elsevier
KW  - Ingeniería de sistemas
KW  - Tool wear
KW  - Texture description
KW  - Patches
KW  - Wear region
TI  - Tool wear monitoring using an online, automatic and low cost system based on local texture
DO  - 10.1016/j.ymssp.2018.04.035
VL  - 112
ER  -