Development of a neural network based surface roughness prediction system using cutting parameters and an accelerometer in turning
Küçük Resim Yok
Tarih
2010
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this work, a technique is proposed to predict surface roughness by using neural network. Surface roughness could be predicted within a reasonable degree of accuracy by taking feed rate, cutting speed, depth of cut and three orthogonal axis (x, y, z) signals of vibrations of tool holder as input parameters. 27 experiments were performed by using a CNC lathe with a carbide cutting tool. Experimental data obtained from turning process were used for training and testing of neural network architecture based prediction system. When experimental and prediction results were compared, it has been seen that a mean accuracy of 91,17% was achieved. © 2010 IEEE.
Açıklama
The MathWorks;PowerWorld Corporation
2010 IEEE International Conference on Electro/Information Technology, EIT2010 -- 20 May 2010 through 22 May 2010 -- Normal, IL -- 82572
2010 IEEE International Conference on Electro/Information Technology, EIT2010 -- 20 May 2010 through 22 May 2010 -- Normal, IL -- 82572
Anahtar Kelimeler
Neural network, Surface roughness, Vibration
Kaynak
2010 IEEE International Conference on Electro/Information Technology, EIT2010
WoS Q Değeri
Scopus Q Değeri
N/A
