Tool wear mechanism and prediction in milling TC18 titanium alloy using deep learning

•The tool wear mechanism in milling TC18 titanium alloy was studied.•The tool wear prediction model is established based on deep learning.•The raw sensory data can be directly used as the input of the model without any feature engineering processing.•CNN + GRU has not been used in tool wear predicti...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Measurement : journal of the International Measurement Confederation 2021-03, Vol.173, p.108554, Article 108554
Hauptverfasser:	Ma, Junyan, Luo, Decheng, Liao, Xiaoping, Zhang, Zhenkun, Huang, Yi, Lu, Juan
Format:	Artikel
Sprache:	eng
Schlagworte:	Aluminum oxide Chemical elements Convolutional bi-directional gated recurrent unit Convolutional bi-directional long short-term memory network Cutting force Cutting tools Cutting wear Deep learning Diffusion layers Oxidation Prediction models Production costs TC18 Titanium Titanium alloys Titanium base alloys Tool wear Tool wear mechanism Wear mechanisms Wear resistance
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!