Cargando…
Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition
Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool con...
Autor principal: | Caggiano, Alessandra |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876750/ https://www.ncbi.nlm.nih.gov/pubmed/29522443 http://dx.doi.org/10.3390/s18030823 |
Ejemplares similares
-
Investigation of the Wear Performance of TiB(2) Coated Cutting Tools during the Machining of Ti6Al4V Alloy
por: Chowdhury, Mohammad Shariful Islam, et al.
Publicado: (2021) -
Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation
por: Segreto, Tiziana, et al.
Publicado: (2017) -
Fundamental Investigation into Tool Wear and Surface Quality in High-Speed Machining of Ti6Al4V Alloy
por: Abbas, Adel T., et al.
Publicado: (2021) -
PEM-PCA: A Parallel Expectation-Maximization PCA Face Recognition Architecture
por: Rujirakul, Kanokmon, et al.
Publicado: (2014) -
Wear Mechanisms and Wear Model of Carbide Tools during Dry Drilling of CFRP/TiAl6V4 Stacks
por: Alonso Pinillos, Unai, et al.
Publicado: (2019)