Naslov
Tool Wear Monitoring Using Radial Basis Function Neural Network

Autori
Brezak, Danko ; Udiljak, Toma ; Mihoci, Kristijan ; Majetić, Dubravko ; Novaković, Branko ; Kasać, Josip

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of International Joint Conference on Neural Networks - IJCNN 2004 / Szolgay, Péter - Budimpešta : Institute of Electrical and Electronics Engineers (IEEE), 2004, 1859-1863

Skup
IJCNN 2004 - International Joint Conference on Neural Networks

Mjesto i datum
Budimpešta, Mađarska, 25.07.2004. - 29.07.2004

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Tool wear monitoring; Radial Basis Function Neural Network; Milling

Sažetak
This paper considers the application of Radial Basis Function neural network (RBFNN) for tool wear determination in the milling process. Tool wear, i.e. flank wear zone widths, have been estimated in two phases using two types of RBFNN algorithms. In the first phase, RBFNN pattern recognition algorithm is used in order to classify tool wear features in three wear level classes (initial, normal and rapid tool wear). On behalf of these results, in the second phase, RBFNN regression algorithm is utilized to estimate the average amount of flank wear zone widths. Tool wear features were extracted in time and frequency domain from three different types of signals: force, acoustic emission and nominal currents of feed drives.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo

POVEZANOST RADA